From 204699dab7967f4a6b0a2a94b3d8e2589c2e392b Mon Sep 17 00:00:00 2001 From: Tiago Date: Wed, 16 Sep 2015 00:06:31 -0400 Subject: [PATCH] Add plain text conversions of .tex files For simplicity, we used detex (`brew install detex` on the mac): `detex -n ./tex/01-intro.tex > ./plain/01-intro.txt` (...) --- plain/01-intro.txt | 482 +++ plain/02-working.txt | 913 ++++++ plain/03-extending.txt | 264 ++ plain/04-gui.txt | 1059 +++++++ plain/05-commands.txt | 6703 ++++++++++++++++++++++++++++++++++++++++ plain/06-shortcuts.txt | 278 ++ plain/07-credits.txt | 249 ++ plain/08-biblio.txt | 4396 ++++++++++++++++++++++++++ plain/09-about.txt | 131 + 9 files changed, 14475 insertions(+) create mode 100644 plain/01-intro.txt create mode 100644 plain/02-working.txt create mode 100644 plain/03-extending.txt create mode 100644 plain/04-gui.txt create mode 100644 plain/05-commands.txt create mode 100644 plain/06-shortcuts.txt create mode 100644 plain/07-credits.txt create mode 100644 plain/08-biblio.txt create mode 100644 plain/09-about.txt diff --git a/plain/01-intro.txt b/plain/01-intro.txt new file mode 100644 index 0000000..38e457a --- /dev/null +++ b/plain/01-intro.txt @@ -0,0 +1,482 @@ + +Getting Startedpart:Getting-Started + +This part provides basic information on ImageJ installation, troubleshooting +and update strategies. It discusses sub:Fiji-introFIJIFiji Is Just ImageJ +and sub:ImageJ2intro as well as third-party software related +to ImageJ. Being impossible to document all the capabilities of ImageJ +without exploring technical aspects of image processing, external +resources allowing willing readers to know more about digital signal +processing are also provided. + + +Introductionsec:What-is-ImageJ? + +ImageJ is a http://rsb.info.nih.gov/ij/disclaimer.htmlpublic domain +Java image processing and analysis program inspired by http://rsb.info.nih.gov/nih-image/NIH Image +for the Macintosh. It runs, either as an online applet or as a downloadable +application, on any computer with a Java1.5 or later virtual machine. +http://imagej.nih.gov/ij/download.htmlDownloadable distributions +are available for Windows, Mac OSX and Linux. It can display, edit, +analyze, process, save and print 8-bit, 16-bit and 32-bit images. +It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, +FITS and 'raw'. It supports 'stacks' (and hyperstacks), a series +of images that share a single window. It is multithreaded, so time-consuming +operations such as image file reading can be performed in parallel +with other operations(A somehow outdated list of ImageJ's features is available at http://imagej.nih.gov/ij/features.html). + +It can calculate area and pixel value statistics of user-defined selections. +It can measure distances and angles. It can create density histograms +and line profile plots. It supports standard image processing functions +such as contrast manipulation, sharpening, smoothing, edge detection +and median filtering. + +It does geometric transformations such as scaling, rotation and flips. +Image can be zoomed up to 32:1 and down to 1:32. All analysis +and processing functions are available at any magnification factor. +The program supports any number of windows (images) simultaneously, +limited only by available memory. + +Spatial calibration is available to provide real world dimensional +measurements in units such as millimeters. Density or gray scale calibration +is also available. + +ImageJ was designed with an open architecture that provides extensibility +via Java plugins. Custom acquisition, analysis and processing plugins +can be developed using ImageJ's built in editor and Java compiler. +User-written plugins make it possible to solve almost any image processing +or analysis problem. + +Being public domain open source software, an ImageJ user has the http://wikieducator.org/The_right_license/The_essential_freedomsfour essential freedoms +defined by the Richard Stallman in 1986: 1) The freedom to run the +program, for any purpose; 2) The freedom to study how the program +works, and change it to make it do what you wish; 3) The freedom to +redistribute copies so you can help your neighbor; 4) The freedom +to improve the program, and release your improvements to the public, +so that the whole community benefits. + +ImageJ is being developed on Mac OSX using its built in editor +and Java compiler, plus the BBEdit editor and the Ant +build tool. The source code is freely http://imagej.nih.gov/ij/developer/source/index.htmlavailable. +The author, Wayne Rasband (mailto:wsr@nih.govwsr@nih.gov), +is a Special Volunteer at the National Institute of Mental Health, +Bethesda, Maryland, USA. + +http://imagejdev.org/historyHistory of ImageJ at imagejdev.org + + +Installing and Maintaining ImageJsec:Updating-ImageJUpdates + +ImageJ can be downloaded from http://imagej.nih.gov/ij/download.html. +Details on how to install ImageJ on Linuxhttp://imagej.nih.gov/ij/docs/install/linux.htmlLinux, +http://imagej.nih.gov/ij/docs/install/mac.htmlMac OS 9, +Mac OS Xhttp://imagej.nih.gov/ij/docs/install/osx.htmlMac OS X +and Windows (OS)http://imagej.nih.gov/ij/docs/install/windows.htmlWindows +C-WindowsInstaller are available at http://imagej.nih.gov/ij/docs/install/ +(Helpsub:Installation... command). +Specially useful are the platform-specific Troubleshooting +and Known Problems sections. Fijisub:Fiji-intro +installation is described at http://fiji.sc/wiki/index.php/Downloads. + +The downloaded package may not contain the latest bug fixes so it +is recommended to upgrade ImageJ right after a first installation. +UpdatesUpdating IJIJImageJ consists only +of running Helpsub:Update-ImageJ..., +which will install the latest http://imagej.nih.gov/ij/upgrade/ij.jar +in the ImageJ folder (on Linux and Windows) or inside the ImageJ.app +(on Mac OSX). + +Helpsub:Update-ImageJ... can +be used to upgrade (or downgrade) the ij.jar file to release +updates or daily builds. Release updates are announced frequently +on the http://imagej.nih.gov/ij/notes.htmlIJ news website +and are labelled alphabetically (e.g., v.1.43m). Typically, these +releases contain several new features and bug fixes, described in +detail on the http://imagej.nih.gov/ij/notes.htmlImageJ News page. +Daily builds, on the other hand, are labelled with numeric +sub-indexes (e.g., v.1.43n4) and are often released without documentation. +Nevertheless, if available, release notes for daily builds can be +found at http://imagej.nih.gov/ij/source/release-notes.html. +When a release cycle ends (v.1.42 ended with 1.42q, v.1.43 with +1.43u, etc.) an installation package is created, downloadable +from http://imagej.nih.gov/ij/download.html. Typically, this +package is bundled with a small list of add-ons (sub:Macros-ExtendingIJ, +sub:Scripts and sub:Plugins). + +http://imagej.nih.gov/ij/macros/toolsets/Luts20Macros20and20Tools20Updater.txtLuts, Macros and Tools Updater, +a macro toolset that performs live-updating of http://imagej.nih.gov/ij/macros/macros +listed on the ImageJ web site + + +ImageJDistributionssec:ImageJ-Distributions + +ImageJ alone is not that powerful: it's real strength is the vast +repertoire of sub:Plugins that extend ImageJ's functionality +beyond its basic core. The many hundreds, probably thousands, freely +available plugins from contributors around the world play a pivotal +role in ImageJ's successCollins:2007p13684. Running Helpsub:Update-ImageJ..., +however, will not update any of the plugins you may have installed(Certain plugins, however, provide self-updating mechanisms (e.g., +http://simon.bio.uva.nl/objectj/ObjectJ and the Bio-Formatshttp://loci.wisc.edu/software/bio-formatsOME Bio-Formats).). + +ImageJ add-ons (sub:Plugins, sub:Scripts and +sub:Macros-ExtendingIJ) are available from several sources +(http://imagej.nih.gov/ij/plugins/ImageJ's plugins page +[Helpsub:Plugins...], +http://imagejdocu.tudor.lu/doku.php?id=plugin:startImageJ Information and Documentation Portal +and http://fiji.sc/wiki/index.php/Category:PluginsFiji's webpage, +among others) making manual updates of a daunting task. This reason +alone, makes it extremely convenient the use of sec:ImageJ-Distributions +bundled with a pre-organized collection of add-ons. + +Below is a list of the most relevant projects that address the seeming +difficult task of organizing and maintaining ImageJ beyond its basics. +If you are a life scientist and have doubts about which distribution +to choose you should opt for sub:Fiji-intro. It is heavily +maintained, offers an automatic updater, improved scripting capabilities +and ships with powerful plugins. More specialized adaptations of ImageJ +are discussed in sub:Other-Software-Packages. + + +Fijisub:Fiji-intro + +http://fiji.sc/FijiFiji (Fiji Is Just ImageJ-Batteries +included) is a distribution of ImageJ together with Java, Java 3D +and several plugins organized into a coherent menu structure. Citing +its developers, "Fiji compares to ImageJ as Ubuntu compares to Linux". +The main focus of Fiji is to assist research in life sciences, targeting +image registration, stitching, segmentation, feature extraction and +3D visualization, among others. It also supports many scripting languages +(BeanScript, Clojure, Jython, Python, Ruby, see sec:ScriptingOtherLang). +Importantly, Fiji ships with a http://fiji.sc/wiki/index.php/Update_Fijiconvenient updater +that knows whether your files are up-to-date, obsolete or locally +modified. http://fiji.sc/wiki/index.php/DocumentationComprehensive documentation +is available for most of its plugins. The Fiji project was presented +publicly for the first time at the http://imagejconf.tudor.lu/doku.phpImageJ User and Developer Conference +in November 2008. + + +MBF ImageJsub:MBFImageJintro + +The MBF ImageJImageJ for Microscopy@ImageJ for Microscopy MBF ImageJ,http://www.macbiophotonics.ca/imagej/MBF ImageJ bundle +or ImageJ for Microscopy (formerly http://www.uhnres.utoronto.ca/facilities/wcif/imagej/WCIF-ImageJ) +features a collection of plugins and macros, collated and organized +by Tony Collins at the MacBiophotonics facility, McMaster University. +It is accompanied by a http://www.macbiophotonics.ca/imagej/comprehensive manual +describing how to use the bundle with light microscopy image data. +It is a great resource for microscopists but is not maintained actively, +lagging behind the development of core ImageJ. + +Note that you can add plugins from MBF ImageJ to Fiji, combining the +best of both programs. Actually, you can use multiple ImageJ distributions +simultaneously, assemble your own ImageJ bundle by gathering the plugins +that best serve your needs (probably, someone else at your institution +already started one?) or create symbolic links to share plugins between +different installations. + +Description of all ImageJ related projects at http://imagejdev.org/faqn141ImageDev + + +Related Softwaresub:Related-Software + + +Software Packages Built on Top of ImageJsub:Other-Software-Packages +description +[Bio7] http://bio7.org/Bio7 is an integrated development +environment for Bio7ecological modeling with a main focus +on individual based modeling and spatially explicit models. Bio7 features: +Statistical analysis (using R); Spatial statistics; Fast communication +between R (GNU S)@R (GNU S) Interoperability,R and +Java; BeanShell and Groovy support; Sensitivity analysis with an embedded +flowchart editor and creation of 3D OpenGL (Jogl) models (see +also RImageJ in sec:ImageJ-Interoperability). +[BoneJ] http://bonej.org/BoneJ BoneJis a collection +of tools for trabecular geometry and whole bone shape analysis. +[Manager] http://www.micro-manager.org/Micro-Manager +is a software package for control of automated microscopes. It lets +you execute common microscope image acquisition strategies such as +time-lapses, multi-channel imaging, z-stacks, and combinations thereof. +Micro@ManagerManager works with microscopes +from all four major manufacturers, most scientific-grade cameras and +many peripherals used in microscope imaging. +[MRI-CIA] http://www.mri.cnrs.fr/index.php?m=38MRI Cell Image Analyzer, +developed by the Montpellier RIO Imaging facility (CNRS), is a rapid +image analysis application development framework, adding visual scripting +interface to ImageJ's capabilities. It can create batch applications +as well as interactive applications. The applications include the +topics DNA combing, quantification +of stained proteins in cells, comparison +of intensity ratios between nuclei and cytoplasm +and counting nuclei stained in different channels". +[ObjectJ] http://simon.bio.uva.nl/objectj/index.htmlObjectJ, +the successor of http://simon.bio.uva.nl/Object-Image/object-image.htmlobject-image, +supports graphical vector objects that non-destructively mark images +on a transparent layer. Vector objects can be placed manually or by +macro commands. Composite objects can encapsulate different color-coded +marker structures in order to bundle features that belong together. +ObjectJ provides back-and-forth navigation between results and images. +The results table supports statistics, sorting, color coding, qualifying +and macro access. +[SalsaJ] http://www.euhou.net/index.php?option=com_content&task=view&id=7&Itemid=9SalsaJ +is a student-friendly software developed specifically for the http://www.euhou.net/EU-HOU project. +It is dedicated to image handling and analysis of astronomical images +in the classroom. SalsaJSalsaJ has been translated into several +languages. +[misc:TrakEM2TrakEM2] http://www.ini.uzh.ch/ acardona/trakem2.htmlTrakEM2 +is a program for morphological Data mining@Data mining TrakEM2,data +mining, three-dimensional Modeling@Modeling TrakEM2 and Bio7,modeling +and image stitching, registration, editing and annotationCardona:2010p18306. +TrakEM2FijiTrakEM2 is http://fiji.sc/wiki/index.php/TrakEM2distributed with Fiji +and http://www.ini.uzh.ch/ acardona/trakem2_manual.htmlcapable of: + + +description +[3D modeling] Objects in 3D, defined by sequences of contours, +or profiles, from which a skin, or mesh, can be constructed, and visualized +in 3D. +[Relational modeling] The extraction of the map that describes +links between objects. For example, which neuron contacts which other +neurons through how many and which synapses. +description +description +BioImageXDhttp://www.bioimagexd.net/BioImageXD, +Endrovhttp://www.endrov.net/Endrov, Image SXMhttp://www.liv.ac.uk/7Esdb/ImageSXM/Image SXM + + +ImageJ Interoperabilitysec:ImageJ-Interoperability + +Several packages exist that allow ImageJ to Interoperabilityinteract +with other applications/environments: +description +[Bitplane Imaris] http://www.bitplane.com/go/products/imarisxtImarisXT +can load and execute ImageJ plugins. Imarishttp://www.bitplane.com/go/products/imarisxt/xtensions/imagejbpImarisAdapter +(Windows only and requiring valid licenses for Imaris and ImarisXT) +allows the exchange of images between Imaris and ImageJ. +[CellProfiler] CellProfiler@CellProfiler Interoperability,http://www.cellprofiler.org/CellProfiler +Carpenter:2006p1986 features http://cellprofiler.org/CPmanual/RunImageJ.htmlRunImageJ, +a module that allows ImageJ plugins to be run in a CellProfiler pipeline. +[Icy] http://www.bioimageanalysis.org/icy/Icy, an open +source community software for Icybio-imaging, executes ImageJ +plugins with almost 100 plugin compatibility. +[Knime] Knime http://knime.org/Knime (KnimeKonstanz Information MinerKonstanz +Information Miner) contains several image processing nodes (KNIPKnime Image Processinghttp://tech.knime.org/community/image-processingKNIPKNIP@KNIP Knime,) +that are capable of executing ImageJ plugins and macros. +[Open Microscopy Environment] OMEOpen Microsopy EnvironmentAll +http://www.openmicroscopy.org/Open Microscopy Environment +projects such as Bio-Formatshttp://www.openmicroscopy.org/site/products/bio-formatsBio-Formats, +http://www.openmicroscopy.org/site/products/visbioVisBio +and http://www.openmicroscopy.org/site/products/omeroOMERO +integrate well with ImageJ. +[RImageJ - R bindings for ImageJ] Bindings between +ImageJ and R (GNU S)@R (GNU S) Interoperability,http://www.r-project.org/R (GNU S) +- The free software environment for statistical computing and graphics. +The documentation for RImageJ is available at http://cran.r-project.org/web/packages/RImageJ/RImageJ.pdf +(see also Bio7 in sub:Other-Software-Packages). +[MIJ - Matlab-ImageJ bi-directional communication] A +Java package for bi-directional data exchange between MATLAB@MATLAB Interoperability,Matlab +and ImageJ, allowing to exchange images between the two imaging software. +MIJ@MIJ Interoperability,MIJ also allows MATLAB to +access all built-in functions of ImageJ as well as third-party ImageJ +plugins. The developers provide more information on the http://bigwww.epfl.ch/sage/soft/mij/MIJ +and http://www.mathworks.com/matlabcentral/fileexchange/32344-hardware-accelerated-3d-viewer-for-matlabMatlab File Exchange +websites. sub:Fiji-intro features http://fiji.sc/wiki/index.php/MijiMiji.m, +which makes even more convenient to use the libraries and functions +provided by Fiji's components from within Matlab. +description +http://imagej.nih.gov/ij/links.htmlImageJ related links, +list of http://developer.imagej.net/category/web-links/related-imaging-softwarerelated imaging software +on the sub:ImageJ2intro website + + +ImageJ2sub:ImageJ2intro + +http://imagejdev.org/ImageJDev is a http://imagejdev.org/fundingfederally funded, +http://imagejdev.org/collaboratorsmulti-institution project +dedicated to the development of the next-generation version of ImageJ: +"ImageJ2ImageJ2". ImageJ2ImageDev@ImageDev ImageJ2,ImageJ2 +is a complete rewrite of ImageJ, that includes the current, stable +version ImageJ ("ImageJ1") with a compatibility layer so that +old-style plugins and macros can run the same as they currently do +in ImageJ1. Below is a http://imagejdev.org/aimssummary +of the http://imagejdev.org/ImageJDev project aims: +itemize +To create the next generation version of ImageJ and improve its core +architecture based on the needs of the community. +To ensure ImageJ remains useful and relevant to the broadest possible +community, maintaining backwards compatibility with ImageJ1 as close +to 100 as possible. +Expand functionality by interfacing ImageJ with existing open-source +programs. +To lead ImageJ development with a clear vision, avoiding duplication +of efforts +To provide a central online resource for ImageJ: program downloads, +a plugin repository, developer resources and more. +itemize +Be sure to follow the ImageJ2 http://imagejdev.org/recent_changesproject news +and the http://imagejdev.org/blogImageDev blog for updates +on this exciting project. + + +Getting Helpsec:Help-ResourcesHelp resources + + +Help on Image Analysis + +Ethics@Ethics Acceptable manipulation,Acceptable manipulationBelow +is a list of online resources (in no particular order) related to +image processing and scientific image analysis, complementing the +list of http://imagej.nih.gov/ij/links.htmlexternal resources on the IJ web site. + + +Ethics in Scientific Image Processing +itemize +http://www.ori.dhhs.gov/education/products/RIandImages/default.htmlOnline learning Tool for Research Integrity and Image Processing + +This website, created by the http://ori.dhhs.gov/Office of Research Integrity, +explains what is appropriate in image processing in science and what +is not. +http://swehsc.pharmacy.arizona.edu/exppath/micro/digimage_ethics.phpDigital Imaging: Ethics (at the Cellular Imaging Facily Core, SEHSC) + +This website, compiled by Douglas Cromey at the University of Alabama +- Birmingham, discusses thoroughly the topic of digital imaging ethics. +It is recommended for all scientists. The website contains links to +several external resources, including: + + +enumerate +http://www.jcb.org/cgi/reprint/166/1/11What's in a picture? The temptation of image manipulation +(2004) M Rossner and K M Yamada, J Cell Biology 166(1):11-15, doi:10.1083/jcb.200406019 +http://www.nature.com/nature/journal/v439/n7079/full/439891b.htmlNot picture-perfect +(2006), Nature 439, 891-892, doi:10.1038/439891b. +enumerate +itemize + +Scientific Image ProcessingImage processing (help)sub:IP-Resources +itemize +http://fiji.sc/wiki/index.php/IP_PrinciplesWhat you need to know about scientific image processing + +Simple and clear, this sub:Fiji-intro webpage explains +basic aspects of scientific image processing. +http://www.imagingbook.comimagingbook.com + +Web site of Digital Image Processing: An Algorithmic Introduction +using Java by Wilhelm Burger and Mark BurgeBurger:2008p14082. +This technical book provides a modern, self-contained, introduction +to digital image processing techniques. Numerous complete Java implementations +are provided, all of which work within ImageJ. +http://homepages.inf.ed.ac.uk/rbf/HIPR2/Hypermedia Image Processing Reference (HIPR2) + +Developed at the Department of Artificial Intelligence in the University +of Edinburgh, provides on-line reference and tutorial information +on a wide range of image processing operations. +https://ifn.mpi-cbg.de/wiki/ifn/index.php/Imaging_Facility_NetworkIFN wikipage + +The Imaging Facility Network (IFN) in Biopolis Dresden provides access +to advanced microscopy systems and image processing. The website hosts +high quality https://ifn.mpi-cbg.de/wiki/ifn/index.php/Teaching_Materialteaching material +and useful links to external resources. +http://www.stereology.info/stereology.info + +Stereology Information for the Biological Sciences, designed to introduce +both basic and advanced concepts in the field of stereology. +itemize +ImageJ Related Publications on page sec:IJ-related-pub + + +Help on ImageJsub:Getting-Help + +Below is a list of the ImageJ Help resourceshelp resources +that complement this guide (see sec:Guide-Formats). +Specific documentation on advanced uses of ImageJ (macro programming, +plugin development, etc.) is discussed in sec:Extending-ImageJ. +enumerate +The ImageJ http://imagej.nih.gov/ij/docs/online documentation pages + +Can be accessed via the Helpsub:Documentation... +command. +The Fijisub:Fiji-intro webpage: + +http://fiji.sc/ +The ImageJ Information and Documentation Portal (ImageJ wikipage): + +http://imagejdocu.tudor.lu/doku.phphttp://imagejdocu.tudor.lu/doku.php +Video Tutorialstutorials on the ImageJ Documentation Portal +and the Fiji YouTube channel: + +http://imagejdocu.tudor.lu/doku.php?id=video:start&s[]=video +and http://www.youtube.com/user/fijichannel. New ImageJ users +will probably profit from http://imagejdocu.tudor.lu/doku.php?id=video:beginner_help:imagej_beginner_s_tutorialChristine Labno's video tutorial. +The MBF ImageJImageJ for Microscopy manual + +http://www.macbiophotonics.ca/imagej/ +Several online documents, most of them listed at: + +http://imagej.nih.gov/ij/links.html and http://imagej.nih.gov/ij/docs/examples/ +Mailing lists:Mailing lists@Mailing lists Help resources, + +enumerate +ImageJ - http://imagej.nih.gov/ij/list.html + +General user and developer discussion about ImageJ. Can be accessed +via the Helpsub:List-Archives... +command. This list is also mirrored at http://imagej.1557.n6.nabble.com/Nabble +and http://dir.gmane.org/gmane.comp.java.imagejGmane. You +may find it easier to search and browse the list archives on these +mirrors. Specially useful are the feed://rss.gmane.org/topics/excerpts/gmane.comp.java.imagejRSS feeds +and the http://news.gmane.org/gmane.comp.java.imagejframes and threads +view provided by Gmane. +Fiji users - http://groups.google.com/group/fiji-users + +For user discussion specific to sub:Fiji-intro (rather +than core ImageJ). +Fiji-devel - http://groups.google.com/group/fiji-devel + +For developer discussion specific to Fiji. +ImageJ-devel - http://imagejdev.org/mailman/listinfo/imagej-devel + +For communication and coordination of the ImageJDev project. +Dedicated mailing lists for ImageJ related projects + +Described at http://imagejdev.org/mailing-lists . +enumerate +enumerate + +Using Mailing-lists + +If you are having problems with ImageJ, you should inquiry about them +in the appropriated Help resourceslist. The ImageJ mailing +list is an unmoderated forum subscribed by a knowledgeable worldwide +user community with 2000 advanced users and developers. +To have your questions promptly answered you should consider the following: +enumerate +Read the documentation files (described earlier in this section) before +posting. Because there will always be a natural lag between the implementation +of key features and their documentation it may be wise to check briefly +the ImageJ news website (Helpsub:ImageJ-News...). +Look up the mailing list archives (Helpsub:List-Archives...). +Most of your questions may have already been answered. +If you think you are facing a Bug (reporting)@Bug (reporting) Debug,bug +try to upgrade to the latest version of ImageJ (Helpsub:Update-ImageJ...). +You should also check if you are running the latest version of the +Java Virtual Machine for your operating system. Detailed instructions +on how to submit a bug report are found at http://imagej.nih.gov/ij/docs/faqs.html#bug. +Remember that in most cases you can find answers within your own ImageJ +installation without even connecting to the internet since the heuristics +for finding commands or writing macros have been significantly improved +in later versions (see sec:Finding-Commands and +sec:Extending-ImageJ). +As with any other mailing list, you should always follow basic http://en.wikipedia.org/wiki/Netiquettenetiquette, +namely: + +enumerate +Use descriptive subject lines - Re: Problem with Image>Set +Scale command is much more effective than a general Re: Problem. +Stay on topic - Do not post off-topic messages, unrelated to the +message thread. +Be careful when sending attachments - Refrain from attaching large +files. Use, e.g., a http://en.wikipedia.org/wiki/File_hosting_serviceComparison_of_notable_file_hosting_servicesfile hosting service +instead. +Edit replies - You should include only the minimum content that is +necessary to provide a logical flow from the question to the answer, +i.e., quote only as much as absolutely necessary and relevant.enumerate +enumerate + diff --git a/plain/02-working.txt b/plain/02-working.txt new file mode 100644 index 0000000..7ad6437 --- /dev/null +++ b/plain/02-working.txt @@ -0,0 +1,913 @@ + +Working with ImageJpart:Working-with-ImageJ + +This part introduces some basic aspects of ImageJ so that you can +use the software more efficiently. It also introduces some important +terms and concepts used throughout this guide. You may skip it if +you already use the program efficiently and are familiar with terms +such as sub:Virtual-Stacks, sub:Hyperstacks-Intro, +sub:Pseudocolor-Images, sub:Color-Composites +or sub:Composite-selections. + + +Using Keyboard Shortcutssub:Using-Shortcuts + +You'll learn more and more Keyboard@Keyboard Shortcuts and Modifier keys,Shortcutsshortcut +keys as you use ImageJ, because (almost) all shortcuts are listed +throughout ImageJ menus. Similarly, in this guide each command has +its shortcut key listed on its name (flanked by square brackets). +Please note that the notation for these key-bindings is case sensitive, +i.e., Shift-modifiers are not explicitly mentioned (a capital A +means Shift-A) and assumes that Require control key +for shortcuts in EditOptionssub:Misc... +is unchecked (i.e., except when using the IJ sub:ImageJ-Macro-Editor +or the sec:Text-Tool, you won't have to hold down the Control +key to use menu shortcuts). For example, the command Editsub:Invert-=00005BI=00005D +can be evoked by Shift I or Ctrl Shift I if Require control +key for shortcuts is checked. The full list of ImageJ shortcuts (see +sec:Keyboard-Shortcuts) can be retrieved at any time using +the PluginsUtilitiessub:List-Shortcuts... +command. + +There are three Modifier keysmodifier keys in ImageJ: +lyxlist00.00.0000 +[Control] (Command KeyCommand key on +Apple keyboards) Denoted by 'Ctrl'CtrlControl key. In this guide also the Command key in Apple keyboards +or Ctrl in this document. Although a control key is typically present +on Apple keyboards, on a Macintosh computer running ImageJ the Command +key Cmd replaces the functionality of the Control key of other +operating systems. For sake of simplification, 'Ctrl' will always +refer to both throughout this guide. +[Shift] Denoted by 'Shift'ShiftShift key +or Shift in this document. +[Alt] Denoted by 'Alt'AltAlt, Option or Meta key +or Alt in this document. This is also the 'Option' or 'Meta' +key on many keyboards. In ImageJ, it is also used to type special +unit symbols such as (AltM) or (AltShiftA). +lyxlist +sec:Keyboard-Shortcuts, Pluginssub:Shortcuts + +infobox +infobox:Frontmost-windowFrontmost Window and Window Activation + + +In ImageJ, all operations are performed on the active (frontmost) +image (which has its title bar highlighted). If a window is already +open it will activate when its opening command is re-run, e.g., if +the BC window is already opened (ImageAdjustsub:Brightness/Contrast...=00005BC=00005D), +pressing its keyboard shortcut (Shift C) will activate +it. + + +Pressing Enter on any image will bring the fig:The-ImageJ-window +to the foreground. In addition, it is also possible to permanently +place the main window above all other windows (see sub:FloatingMainWin). +infobox + + + +Finding Commandssec:Finding-Commands + +Navigating through the extensive list of ImageJ commands, macros and +plugins may be quite cumbersome. Through its built-in Command Finder/LauncherC-ComandFinder, +ImageJ offers an expedite alternative that allows you to retrieve +commands extremely fast: PluginsUtilitiessub:Command-Finder. + +In addition, ImageJ features a find function that locates macros, +scripts and plugins source (.java) files on your computer: the PluginsUtilitiessub:Search... +command. Because most of IJ source files contain circumstanced comments, +you can use this utility to retrieve files related not only to a image +processing routine (e.g., background or co-localization) +but also to a practical context such as radiogram, cell +or histology. Indeed, ImageJ source files contain detailed +annotations useful to both developers and regular users that want +to know more about ImageJ routines and algorithms. + +sub:Search... and sub:Command-Finder +are described in detail in Pluginssub:Utilities. +figure +centering +11.1emPluginsUtilitiessub:Command-Finder + +centering + +centering +images/CommandFinderAndSearch +centering + +PluginsUtilitiessub:Search... +figure + + +sub:Control-Panel..., sec:Keyboard-Shortcuts +and http://imagej.nih.gov/ij/macros/SourceCodeRetriever.txtSourceCodeRetriever, +a macro that searches for a menu entry and retrieves the source file +of the respective command + + +[Undo and Redo]Undo and Redosec:Undo-and-Redo + +Probably the first thing you will notice is that ImageJ does not have +a large Undoundo/redo buffer. Undo (Editsub:Undo-=00005Bz=00005D) +is currently limited to the most recent image editing/filtering +operation. With time you will appreciate that this is necessary to +minimize memory overhead. Nevertheless, with IJ1.45 and later, +sub:Undo-=00005Bz=00005D is, in most +cases, undoable and can be applied to multiple images if Keep +multiple undo buffers is checked in EditOptionssub:Memory-=000026-Threads... + +If you cannot recover from a mistake, you can always use Filesub:Revert=00005Br=00005D +to reset the image lo its last saved state. For selections, EditSelectionsub:Restore-Selection-=00005BE=00005D +can be used to recover any misdealt selection. + +In ImageJ the equivalent to Redo'Redo' is the Processsub:Repeat-Command-=00005BR=00005D, +that re-runs the previous used command (skipping Editsub:Undo-=00005Bz=00005D +and Filesub:Open... commands). + +PluginsUtilitiessub:Reset..., +http://imagejdocu.tudor.lu/doku.php?id=plugin:utilities:multi_undo:startMulti Undo +plugin + + +Image Types and Formatssec:Image-Types + +Image typesDigital Images are two-dimensional grids of pixelpixelPicture element +intensities values with the width and height of the image being defined +by the number of pixels in (rows) and (columns) direction. +Thus, pixels (picture elements) are the smallest single components +of images, holding numeric values - pixel intensities - that range +between black and white. The characteristics of this range, i.e., +the number of unique intensity (brightness) values that can exist +in the image is defined as the bitbitBinary digit-depth +of the image and specifies the level of precision in which intensities +are coded, e.g.: A 2-bit image has tones: 00 (black), +01 (gray), 10 (gray), and 11 (white). A 4-bit image has tones +ranging from 0000 (0) to 1111 (16), etc. In terms of bits per pixel +(bppbppBits per pixel), the most frequent types +of images (Imagesub:Type) that ImageJ deals +with are (ImageJ2sub:ImageJ2intro supports http://imagejdev.org/imagej2-pixel-typesmany more types of image data): +lyxlistRGB-Color- +[8-bit] Images that can display 256 () +gray levels (integers only). +[16-bit] Images that can display 65,536 +() gray levels (integers only). +[32-bit] Images that can display 4,294,967,296 +() gray levels (real numbers). In 32-bit images, pixels +are described by http://en.wikipedia.org/wiki/Floating_pointfloating point +values and can have any intensity value including NaNNaNNot a Number +(Not a Number). +[RGB Color] sec:Color-Images that +can display 256 values in the Red, Green and +Blue channel. These are 24-bit () images. +RGBRGBRed Green Blue color images can also be 32-bit +color images (24-bit color images with additional eight bits coding +alpha blending values, i.e., transparency). +lyxlist + +Native Formatssub:Native-Formats + +Natively (i.e. without the need of third-party plugins) ImageJ opens +the following formats: TIFFTIFFTagged Image File Format, +GIFGIFGraphics Interchange Format, JPEGJPEGJoint Photographic Experts Group, +PNGPNGPortable Network Graphics, DICOMDICOMDigital Imaging and Communications in Medicine, +BMPBMPBitmap Image File (Device Independent Bitmap, DIB), +PGMPGMPortable GrayMap and FITSFITSFlexible Image Transport System. +Image formats!NativeMany more formats are supported with +the aid of plugins. These are discussed in sub:Non-native-Supported-Formats. +lyxlist00.00.0000 +[TIFF] (Tagged Image File Format) is the 'default' format +of ImageJ (cf. Filesub:Save=00005Bs=00005D). +Images can be 1-bit, 8-bit, 16-bit (unsigned(A numeric variable is signed if it can represent both positive and +negative numbers, and unsigned if it can only represent positive numbers.)), 32-bit (real) or RGB color. TIFFTIFF files with multiple +images of the same type and size open as sub:Stacks-Intro +or sub:Hyperstacks-Intro. ImageJ opens Lossless compressionlossless +compressed TIFF files (see infobox:Formats infobox:Formats) +by the LZWLZWLempel-Ziv-WelchLZW compression, +PackBits compressionPackBits and ZIP!Lossless compressionZIP +(Deflate@Deflate Zip compression,Deflate/Inflate)C-ZIPcompressedTIFFs +compression schemes. In addition, TIFF files can be opened and saved +as ZIP!Archived TIFF filesZIP archives. + +Tiff tags and information needed to import the file (number of images, +offset to first images, gap between images) are printed to the sec:Log-Window +when ImageJ is running in Debug Mode (EditOptionssub:Misc..., +see sec:Settings-and-Preferences). +[DICOM] (Digital Imaging and Communications in Medicine) +is a standard popular in the medical imaging community. Support in +ImageJ is limited to uncompressed DICOMDICOM files. DICOM +files containing multiple images open as sub:Stacks-Intro. + +Use Imagesub:Show-Info... +to display the DICOM header information. A DICOM sequence can be opened +using FileImportsub:Image-Sequence... +or by dragging and dropping the folder on the 'ImageJ' window. Imported +sequences are sorted by image number instead of filename and the tags +are preserved when DICOM images are saved in TIFF format. ImageJ supports +custom DICOM dictionaries, such as the one at http://imagej.nih.gov/ij/download/docs/DICOM_Dictionary.txt. +More information can be found at the http://www.cabiatl.com/mricro/dicom/index.htmlCenter for Advanced Brain Imaging. +[FITS] (Flexible Image Transport System) image is the +format adopted by the astronomical community for data interchange +and archival storage. Use Imagesub:Show-Info... +to display the FITSFITS header. More information http://fits.gsfc.nasa.govhere. +[PGM] (PGMPortable GrayMap), PBMPBMPortable BitMap +(Portable BitMap) and PPMPPMPortable PixMap +(Portable PixMap) are simple image formats that use an ASCIIASCIIAmerican Standard Code for Information Interchange +header. More information http://local.wasp.uwa.edu.au/ pbourke/dataformats/ppm/here. +[AVI] (Audio Video Interleave) is a container format which +can contain data encoded in many different ways. ImageJ only supports +uncompressed AVIAVIs, various YUVYUV 4:2:2 compressed +formats, and PNGPNG or JPEGJPEG-encoded individual +frames. Note that most MJPGMJPGMJPGMotion-JPEG +(motion-JPEG) formats are not read correctly. Attempts to open AVIs +in other formats will fail. +lyxlist +sub:Non-native-Supported-Formats, infobox:Formats +infobox:Formats, infobox:JpegAlert infobox:JpegAlert + + +Non-native Formats sub:Non-native-Supported-Formats + +When opening a file, ImageJ first checks whether it can natively handle +the format. Image formats!Non-nativeIf ImageJ does not recognize +the type of file it calls for the appropriate reader plugin using +http://imagej.nih.gov/ij/plugins/file-handler.htmlHandleExtraFileTypes, +a plugin bundled with ImageJ. If that fails, it tries to open the +file using the OME Bio-Formats@OME Bio-Formats Bio-Formats,LOCI Bio-Formats@LOCI Bio-Formats Bio-Formats,Bio-formats@Bio-formats LOCI,http://loci.wisc.edu/software/bio-formatsOME Bio-Formats library +(if present), a remarkable plugin that supports more than http://loci.wisc.edu/bio-formats/formatsone hundred of the most common +file formats used in microscopy. If nevertheless the file cannot be +opened, an error message is displayed. + +Because both these plugins are under active development, it is important +that you keep them updated. The OME Bio-Formats library can be updated +using its self-updating plugin (PluginsLOCIUpdate LOCI Plugin) +or Fiji's built-in updater (HelpUpdate Fiji). +The following websites provide more information on the OME Bio-Formats: +itemize +http://loci.wisc.edu/bio-formats/imagejhttp://loci.wisc.edu/bio-formats/imagej +http://fiji.sc/Bio-Formatshttp://fiji.sc/Bio-Formats +http://loci.wisc.edu/bio-formats/using-bio-formatshttp://loci.wisc.edu/bio-formats/using-bio-formats +itemize +In addition, the ImageJ web site lists http://imagej.nih.gov/ij/plugins/iomore than sixty plugins +that recognize more 'exotic' file formats. The ImageJ Documentation +Portal also maintains a (somewhat outdated) http://imagejdocu.tudor.lu/doku.php?id=faq:general:which_file_formats_are_supported_by_imagejlist of file formats +that are supported by ImageJ. + +sub:Native-Formats, Filesub:Import, +infobox:Formats infobox:Formats, infobox:JpegAlert +infobox:JpegAlert, http://imagej.nih.gov/ij/plugins/acqAcquisition plugins, +http://imagej.nih.gov/ij/plugins/ioInput/Output plugins + +infobox +infobox:FormatsImage Types: Lossy Compression and Metadata + + +Two critical aspects to keep in mind when converting images: +description +[misc:LossyCompressionLossy compression] Transcoding +an image into a format that uses Lossy compressionlossy compression +will alter the original data, introducing artifacts (see infobox:JpegAlert +infobox:JpegAlert). This is the case, e.g., for JPEG formats +(with the exception of some JPEG2000@JPEG2000JPEG2000 +images that use lossless compression). As such, these types of data +are intended for human interpretation only and are not suitable for +quantitative analyses +[misc:MetadataMetadata] In ImageJ, Metadatametadata +associated with the image, such as scale, gray value calibration and +user comments is only supported in tiff and zip (compressed tiff) +images. In addition, selections and sub:Overlay-Intro are +also saved in the TIFF header (cf. Filesub:Save=00005Bs=00005D). +None of the above is saved in other formats (cf. sub:Native-Formats).description +infobox + + + +Stacks, Virtual Stacks and Hyperstackssec:StacksVirtualStacksHyperStks + + +Stackssub:Stacks-Intro + +ImageJ can display multiple spatially or temporally related images +in a single window. These image sets are called stacks. The images +that make up a stack are called slices. In Stacksstacks, +a pixel (which represents 2D image data in a bitmap image) becomes +a voxelvoxelVolumetric pixel (volumetric pixel), +i.e., an intensity value on a regular grid in a three dimensional +space. + +All the slices in a stack must be the same size and bit depth. A scrollbar +provides the ability to move through the slices and the slider is +preceded by a play/pause icon that can be used to start/stop stack +animation. Right-clicking on this icon runs the sub:Animation-Options... +dialog box. + +Most ImageJ filters will, as an option, process all the slices in +a stack. ImageJ opens multi-image TIFF files as a stack, and saves +stacks as multi-image TIFFs. The FileImportsub:Import>Raw +command opens other multi-image, uncompressed files. A folder of images +can be opened as a stack either by dragging and dropping the folder +onto the 'ImageJ' window or or by choosing FileImportsub:Image-Sequence... +To create a new stack, simply choose FileNewsub:Image...=00005Bn=00005D +and set the Slices field to a value greater than one. The Imagesub:Stacks +submenu contains commands for common stack operations. +figure +images/StacksHyperstacks[Stacks and Hyperstacks]fig:Stacks-and-HyperstacksStacks and Hyperstacks +in ImageJ: FileOpen SamplesMitosis (26MB, 5D stack). +Hyperstacks dimensionality can be reduced using ImageHyperstackssub:Reduce-Dimensionality..., +ImageStackssub:Z-Project... or ImageHyperstackssub:Channels...=00005BZ=00005D +The '(V)' on the window title denotes a virtual image (see +sub:Virtual-Stacks). +figure + + +sub:StacksMenu, http://fiji.sc/wiki/index.php/Stack_ManipulationStack Manipulations +on Fiji website, http://imagej.nih.gov/ij/plugins/image5d.htmlImage5D + + +Virtual Stackssub:Virtual-Stacks + +Stacks!VirtualVirtual stacks@Virtual stacks Stacks (Virtual),Virtual +stacks are disk resident (as opposed to RAMRAMRandom-Access Memory +resident) and are the only way to load image sequences that do not +fit in RAM. There are several things to keep in mind when working +with virtual stacks: +itemize +Virtual stacks are read-only, so changes made to the pixel data are +not saved when you switch to a different slice. You can work around +this by using macros (e.g., http://imagej.nih.gov/ij/macros/Process_Virtual_Stack.txtProcess Virtual Stack) +or the ProcessBatchsub:Virtual-Stack... +command +You can easily run out of memory using commands like Imagesub:Crop-=00005BX=00005D +because any stack generated from commands that do not generate virtual +stacks will be RAM resident. +TIFF virtual stacks can usually be accessed faster than JPEGJPEG +virtual stacks. A JPEG sequence can be converted to TIFF by opening +the JPEG images as a virtual stack and using FileSave Assub:SaveAs>Image-Seq... +to save in TIFF format +itemize +ImageJ appends a '(V)' to the window title of virtual stacks and +hyperstacks (see sub:Hyperstacks-Intro). Several +built-in ImageJ commands in the Filesub:Import +submenu have the ability to open virtual stacks, namely: sub:Import>TIFF-Virtual-Stack, +sub:Image-Sequence..., sub:Import>Raw, +sub:Stack-From-List..., sub:Import>AVI... +(cf. http://imagej.nih.gov/ij/plugins/virtual-opener.htmlVirtual Stack Opener). +In addition, TIFF stacks can be open as virtual stacks by drag and +drop (cf. infobox:VirtualTiff infobox:VirtualTiff). + +http://www.loci.wisc.edu/ome/formats.htmlLOCI Bio-Formats +and http://fiji.sc/wiki/index.php/Register_Virtual_Stack_SlicesRegisterVirtualStackSlices +plugins, http://imagej.nih.gov/ij/macros/Process_Virtual_Stack.txtProcess Virtual Stack +and http://imagej.nih.gov/ij/macros/VirtualStackFromList.txtVirtualStackFromList +macros + +infobox +infobox:VirtualTiffOpening Virtual Stacks by Drag Drop + + +TIFF stacks with a .tif extension open as virtual +stacks when dragged and dropped on the images/tools/Switcher-small toolbar +icon. + + +images/DragAndDropVirtualTiff +infobox + + + +Hyperstackssub:Hyperstacks-Intro + +Stacks!HyperstacksHyperstacks are multidimensional images, +extending image stacks to four (4D) or five (5D) dimensions: +(width), (height), (slices), (channels or wavelengths) +and (time frames). Hyperstacks are displayed in a window with +three labelled scrollbars (see fig:Stacks-and-Hyperstacks). +Similarly to the scrollbar in sub:Stacks-Intro, the frame +slider (t) has a play/pause icon. + +Imagesub:Hyperstacks submenu + + +[Color Images]Color ImagesThis section is partially extracted from the MBFImageJ online manual +at http://www.macbiophotonics.ca/imagej/colour_image_processi.htm.sec:Color-Images + +MBF ImageJImageJ deals with color mainly in three ways: pseudocolor +images, RGB images, RGB/ HSBHSBHue Saturation Brightness +stacks, and composite images.Image types + + +Pseudocolor Imagessub:Pseudocolor-Images + +A pseudocolor (or indexed color) image is a single channel gray image +(8, 16 or 32-bit) that has color assigned to it via a lookup table +or LUTLUTLookup tableLUT. A LUT is literally +a predefined table of gray values with matching red, green and blue +values so that shadows of gray are displayed as colorized pixels. +Thus, differences in color in the pseudo-colored image reflect differences +in intensity of the object rather than differences in color of the +specimen that has been imaged. + +8-bit indexed color images (such as GIFs) are a special case of pseudocolor +images as their lookup table is stored in the file with the image. +These images are limited to 256 colors (24-bit RGB images allow 16.7 +million of colors, see sec:Image-Types) and concomitantly +smaller file sizes. Reduction of true color values to a 256 Color palette@Color palette LUT,color +palette is performed by color quantization algorithms. ImageJ uses +the Color!QuantizationHeckbert quantizationAlgorithm!Heckbert quantizationHeckbert's +median-cut color quantization algorithm (see Imagesub:Type +menu), which, in most cases, allows indexed color images to look nearly +identical to their 24-bit originals. + +Imagesub:Lookup-Tables and sub:LUTMenu + + +True Color Imagessub:True-color-images + +As described in sec:Image-Types, true color images such +as RGB images reflect genuine colors, i.e., the green in an RGB image +reflects green color in the specimen. Color images are typically produced +by color CCDCCDCharge-Coupled Device cameras, in +which Color filter arraycolor filter arrays (http://en.wikipedia.org/wiki/Bayer_filterBayer masks) +are placed over the image sensor.CCD + + +Color Spaces and Color Separationsub:Color-Spaces-and + +http://en.wikipedia.org/wiki/Color_spaceColor spaces Color!Modelsdescribe +the gamut of colors that image-handling devices deal with. Because +human vision is trichromatic, most color models represent colors by +three values. Mathematically, these values (color components) form +a three-dimensional space such as the RGBRGB, HSBHSB, +CIE LabCIELab or YUVYUV color space. +figure[h] +images/RGB-HSBcolorModels[RGB and HSB color models]fig:ColorModelsRepresentation of an eight pixel +color image in the RGB and HSB color spaces. The RGB color space +maps the RGB color model to a cube with Red (R) values increasing +along the x-axis, Green (G) along the y-axis and Blue +(B) along the z-axis. In the HSB cylindrical coordinate system, the +angle around the central vertical axis corresponds to Hue (H), +the distance from the axis corresponds to Saturation (S), and +the distance along the axis corresponds to Brightness (B). +In both cases the origin holds the black color. The right panel shows +the same image after brightness reduction, easily noted by the vertical +displacement along the HSB cylinder. Images produced using Kai Uwe +Barthel's http://www.f4.fhtw-berlin.de/ barthel/ImageJ/ColorInspector//help.htm3D Color Inspector +plugin. +figure + + +RGB (Red, Green, Blue) is the most +commonly-used color space. However, other alternatives such as HSB +(Hue, Saturation, Brightness) provide +significant advantages when processing color information. In the HSB +color space, Hue describes the attribute of pure color, and +therefore distinguishes between colors. Saturation (sometimes +called "purity" or "vibrancy") characterizes the shade of +color, i.e., how much white is added to the pure color. Brightness +(also know as Value - HSV system) describes the overall brightness +of the color (see e.g., the color palette of fig:CPtool). +In terms of digital imaging processing, using the HSB system over +the traditional RGB is often advantageous: e.g., since the Brightness +component of an HSB image corresponds to the grayscale version of +that image, processing only the brightness channel in routines that +require grayscale images is a significant computational gain(See Wootton R, Springall DR, Polak JM. Image Analysis in Histology: +Conventional and Confocal Microscopy. Cambridge University Press, +1995, ISBN 0521434823). You can read more about the HSB color model http://en.wikipedia.org/wiki/HSB_color_spacehere. + +In ImageJ, conversions between image types are performed using the +Imagesub:Type submenu. Segmentation +on the HSB, RGB, CIELab and YUV color spaces can be performed by +the ImageAdjustsub:Color-Threshold... +commandC-ColorThres. Segregation of color components (specially +useful for quantification of Color!DeconvolutionColor!Separation@Separation Color!Deconvolution,Immunohistochemistry@Immunohistochemistry Histochemical staining,histochemical +staining) is also possible using Gabriel Landini's http://www.dentistry.bham.ac.uk/landinig/software/cdeconv/cdeconv.htmlColour Deconvolution +plugin. In addition, several other plugins related to color processing +can be obtained from the http://imagej.nih.gov/ij/plugins/index.htmlcolorImageJ website. + + +Conveying Color InformationThis section is partially extracted from Masataka Okabe and Kei Ito, +Color Universal Design (CUD) - How to make figures and presentations +that are friendly to Colorblind people, http://jfly.iam.u-tokyo.ac.jp/color/, +accessed 2009.01.15sub:Conveying-Color-Information + +People see color with significant variations. Indeed, the popular +phrase "One picture is worth ten thousand words" may not apply +to certain color images, specially those that do not follow the basic +principles of http://jfly.iam.u-tokyo.ac.jp/color/Color Universal Design. +Citing Masataka Okabe and Kei Ito: +quotation +Color!BlindnessColorblind people can recognize a wide ranges +of colors. But certain ranges of colors are hard to distinguish. The +frequency of colorblindness is fairly high. One in 12 Caucasian (8), +one in 20 Asian (5), and one in 25 African (4) males are so-called +'red-green' colorblind. + +There are always colorblind people among the audience and readers. +There should be more than ten colorblind in a room with 250people +(assuming 50 male and 50 female). + +[] There is a good chance that the paper you submit +may go to colorblind reviewers. Supposing that your paper will be +reviewed by three white males (which is not unlikely considering the +current population in science), the probability that at least one +of them is colorblind is whopping 22! +quotation +figure +images/Dichromacy[Red-green images and partial color blindness]fig:ColorBlindnessRed-green images and partial +color blindness. Deuteranopia (second panel), protanopia (third panel) +are the most common types of partial color blindness (red/green +confusion). Tritanopia (blue/orange confusion, fourth panel) +is quite rare. infobox:Replacing-Red-w-Magenta (bottom +row) is a simple way to compensate for color vision deficiencies. +figure +One practical point defined by the http://jfly.iam.u-tokyo.ac.jp/color/Color Universal Design +is the use of magenta in red-green overlays (see alsoLandini:2009p19625). +Magenta is the equal mixture of red and blue. Colorblind people that +have difficulties recognizing the red component can easily recognize +the blue hue. The region of double positive becomes white, which is +easily distinguishable for colorblind. In ImageJ this is easily accomplished +using the ImageColorsub:Merge-Channels..., +or using the ImageJ macro language (see infobox:Replacing-Red-w-Magenta +infobox:Replacing-Red-w-Magenta). +infobox +infobox:Replacing-Red-w-MagentaReplacing Red with Magenta +in RGB Images + + +When building RGB images, magenta can be obtained using the ImageColorsub:Merge-Channels... +Previously created RGB images can be converted to Magenta Green Blue (MGB)'MGB' +using ImageColorsub:Channels...=00005BZ=00005D. +Alternatively, the Processsub:Image-Calculator... +command can be used to add the red channel to the blue channel. Both +these approaches can be automated using the ImageJ macro language +as exemplified by Macros lis:RGBtoMGB1 and lis:RGBtoMGB2. +Once saved in the ImageJ/plugins/ folder these sub:Macros-ExtendingIJ +are treated as regular ImageJ commands. + + +In sub:Fiji-intro, as expected, the procedure of modifying +RGB images is simpler: one just needs to run ImageColorReplace Red with Magenta. +For even more convenience, Fiji provides an analogous command that +replaces the system clipboard's image with a magenta-green one. +infobox + + +It is also possible to simulate color blindness using the http://www.vischeck.com/downloads/Vischeck +or http://www.dentistry.bham.ac.uk/landinig/software/dichromacy/dichromacy.htmlDichromacy +plugins(One advantage of Dichromacy over the Vischeck plugin is that it can +be recorded and called from scripts and macros, without user interaction.), or in Fijisub:Fiji-intro, using the ImageColorSimulate Color Blindness +command. +lstlisting[caption=ReplaceRedwithMagenta.ijm (Using ProcessImage Calculator),label=lis:RGBtoMGB2,float=h,showstringspaces=false,tabsize=4] + /* This macro replaces Red with Magenta in RGB images using Process>Image Calculator... command. */ + if (bitDepth!=24) + exit("This macro requires an RGB image"); + setBatchMode(true); + title= getTitle(); + r= title+" (red)"; g= title+" (green)"; b= title+" (blue)"; + run("Split Channels"); + imageCalculator("Add", b, r); + run("Merge Channels...", "red=&r green=&g blue=&b"); + rename(title + " (MGB)"); + setBatchMode(false); +lstlisting + + + +Color Composite Imagessub:Color-Composites + +In a Color!Compositescomposite image colors are handled through +channels. The advantages with this type of image over plain RGB images +are: +enumerate +Each channel is kept separate from the others and can be turned on +and off using the 'Channels' tool (ImageColorsub:Channels...=00005BZ=00005D). +This feature allows, e.g., to perform measurements on a specific channel +while visualizing multiple. +Channels can be 8, 16 or 32-bit and can be displayed with any lookup +table +More than 3channels can be merged or kept separate +enumerate +lstlisting[caption=ReplaceRedwithMagenta.ijm (Using ImageColorChannels),label=lis:RGBtoMGB1,float=h,showstringspaces=false,tabsize=4] + /* This macro replaces Red with Magenta in RGB images using the Image>Color>Channels... tool. */ + if (bitDepth!=24) // Ignore non-RGB images + exit("This macro requires an RGB image"); + setBatchMode(true); // Enter 'Batch' mode + title = getTitle(); // Retrieve the image title + run("Make Composite"); // Run Image>Color>Make Composite + run("Magenta"); // Run Image>Lookup Tables>Magenta on channel 1 + run("RGB Color"); // Run Image>Type>RGB Color + rename(title + " (MGB)"); // Rename the image + setBatchMode(false); // Restore 'GUI' mode +lstlisting + + + +Selectionssec:Selections-Intro + +Selections (regions of interest, ROIsROIRegion Of Interest), +are typically created using the sub:Toolbar sec:IJ-Tools. +Although ImageJ can display simultaneously several SelectionROI@ROI Selection,ROIs +(see sub:Overlay-Intro and fig:The-ROI-Manager) +only one selection can be active at a time. Selections can be measured +(Analyzesub:Measure...=00005Bm=00005D), +drawn (Editsub:Draw-=00005Bd=00005D), +filled (Editsub:Fill-=00005Bf=00005D) +or filtered (Processsub:Filters submenu), +in the case of area selections. In addition it is also possible to +hold multiple ROIs as non-destructive sub:Overlay-Intro. + +Selections can be initially outlined in one of the nine ImageJ default +colors (Red, Green, Blue, Magenta, Cyan, +Yellow, Orange, Black and White). Once created, +selections can be contoured or painted with any other color using +EditSelectionsub:Properties.... +Selection Color can be changed in EditOptionssub:Colors..., +by double clicking on the sec:Point-Tool, or using hot +keys (see lis:ChangeSelectionColor lis:ChangeSelectionColor). +It is highlighted in the center of the sec:Point-Tool and +sec:Multi-point-Tool. +figure[h] +images/Selectionsfig:exampleAreaROIsThree types of area selections +In ImageJ. Notice the cursor changes: to an arrow when it +is within the selection, to a cross-hair when outside the selection, +to a hand when over a selection vertex or 'handler'. Notice +also the filled handler in the polygon selection and the absence of +point handlers in sub:Composite-selections. sub:Overlay-Intro, +i.e., non-active selections displayed in the non-destructive image +overlay, are also displayed without handlers. +figure + + + +Manipulating ROIssub:Manipulating-ROIs + +Most of commands that can be useful in defining or drawing selections +are available in the Editsub:SelectionSubMenu +submenu and summarized in fig:ROI-manipulations. Listed +below are the most frequent manipulations involving ROI@ROI Selection,selections: +lyxlist00000000000 +[Adjusting] Area selections can be adjusted +with the sub:Brush-Selection-Tool. In addition, vertexes +of selections created with the sub:Polygon-Selection-Tool +and sub:Segmented-Line-Selection can be adjusted by Alt/Shift-clicking. +[Deleting] Choose any of the selection tools +and click outside the selection, or use EditSelectionsub:Select-None-=00005BA=00005D. +Use EditSelectionsub:Restore-Selection-=00005BE=00005D +to restore a selection back after having deleted it. With sub:Overlay-Intro, +an activated ROI can be deleted by pressing the Backspace +(Delete on Mac) key. +[Managing] A selection can be transferred from +one image window to another by activating the destination window and +runnig EditSelectionsub:Restore-Selection-=00005BE=00005D. +Alternatively, AnalyzeToolssub:SynchronizeWindows +to create ROIs across multiple images. Multiple selections can be +stored as sub:Overlay-Intro or in the fig:The-ROI-Manager +list (AnalyzeToolssub:ROI-Manager...). +[Moving] Selections can be moved by clicking +and dragging as long as the cursor is within the selection and has +changed to an images/pointers/Pointer-Arrow. +The status bar displays the coordinates of the upper left corner of +the selection (or the bounding rectangle for non-rectangular selections) +as it is being moved. To move the contents of a selection, rather +than the selection itself, Editsub:Copy=00005Bc=00005D, +Editsub:Paste=00005Bv=00005D, +and then click within the selection and drag. +[Nudging] Selections can be 'nudged' one pixel +at a time in any direction using the arrow keys. Note that the up +and down keys zoom the image in and out in the absence of selections +(see Arrow-Keys shortcuts). +[Resizing] The sub:Brush-Selection-Tool can +be used to perform fine adjustments of ROI contours. Most ROIs can +be resized one pixel at a time by holding Alt while using the arrow +keys. In general (see sec:Area-selection-tools and +sec:Line-Selection-Tools for details), selections are resized +by dragging one of the selection handlers. While dragging, holding +Ctrl resizes the selection around its center, holding Alt imposes +a fixed aspect ratio and holding Shift forces a 1:1 aspect ratio. +lyxlist +sec:Key-Modifiers + + +Composite Selectionssub:Composite-selections + +wrapfigure[5]l0.245 +images/compositeROIwrapfigure +Composite selections are non-contiguous ROIs containing more than +one cluster of pixels and/or ROIs containing internal holes. Composite +ROIs are typically originated with the sub:Brush-Selection-Tool +but they can be defined with any other selection tool using key modifiers. + +The following modifier keys can be use to create composite selections:Selection!Composite +lyxlistshifttt +[Shift] Drawing outside current selection while pressing +Shift creates new content. To add a non-square rectangle or ellipse, +the Shift key must be released after adding the selection +[Alt] Drawing inside current selection while pressing Alt creates +a hole removing content from the ROI +lyxlist +Note that some operations may not be performed properly on complex +ROIs. In these cases, it may be useful to convert a composite ROI +into a polygon using the EditSelectionsub:Enlarge... +command as explained in infobox:Composites infobox:Composites. + +sub:Wand-Tool, http://imagejdocu.tudor.lu/doku.php?id=wishlist:completed:freehand_and_selection_brush_roi_conversionROI2PolylineROI +macro + + +[Selections With Sub-pixel Coordinates]Selections With Sub-pixel Coordinatessub:Sub-pixel-SelectionsSub-pixel selectionsSelections with sub-pixel resolution + +Since ImageJ 1.46, selections can be defined with http://en.wikipedia.org/wiki/Sub-pixel_resolutionsubpixel accuracy, +beyond the nominal pixel resolution of the image: fig:Subpixel-selections. +Line Selections (see sec:Line-Selection-Tools) are +created with floating-point coordinates if the Sub-pixel resolution +checkbox is active in EditOptionssub:Profile-Plot-Options... +Sub-pixel coordinates of pre-existing selections can be interpolated +using the EditSelectionsub:Interpolate +command. Interpolated points are easily noticeable on small selections +created on images zoomed 1200 or greater. +figure[h] +images/SubPixel[Floating point selections]fig:Subpixel-selectionsInterpolated selections. +ROIs drawn with (left) or without (middle) sub-pixel accuracy. For +line selections (see sec:Line-Selection-Tools), +this option can be enabled in EditOptionssub:Profile-Plot-Options... +by activating the Sub-pixel resolution checkbox. Pixel coordinates +of area selections (see sec:Area-selection-tools), +can be interpolated using EditSelectionsub:Interpolate. +The image on the right is the output of http://imagej.nih.gov/ij/macros/js/SubPixelSelections.jsSubPixelSelections.js, +a script that demonstrates how to create selections at sub-pixel resolution +without the need of setting any option in ImageJ. +figure + + +sub:Zoom, sec:Magnifying-Glass + + +[Overlays]Overlayssub:Overlay-IntroImproved handling of Overlays + +OverlayNon-destructive annotations@Non-destructive annotations Overlay,Annotations!Non-destructive image overlayOverlays +are non-active selections displayed 'over' the pixel data, on the +image overlay, and are the core of non-destructive image processing +in ImageJ. In a way you can think of the image overlay as an invisible +fig:The-ROI-Manager in which selections are being added, +allowing ROIs to be on 'hold'. This concept of multiple distinct +selections has been dramatically improved in sub:ImageJ2intro +so we urge you to download IJ2 if multiple ROIs are important in your +workflows. +figure +images/OverlayShowcaseNon-destructive operations using the image overlay. Overlays +can be used to annotate images, store ROIs and blend images (ImageROIs) +at multiple opacity levels. Refer to the Imagesub:Overlaydocumentation +for further fig:image-overlays. You can http://imagej.nih.gov/ij/docs/guide/images/ImageWithOverlay.tifdownload the frontmost +image to practice overlay editing. +figure + + +Importantly, overlay selections are http://en.wikipedia.org/wiki/Vector_graphicsvector graphics +composed of mathematically-defined paths (as opposed to http://en.wikipedia.org/wiki/Raster_graphicsraster graphics +in which objects are defined by pixels) and are not affected by scaling, +i.e., do not become pixelated. Most of overlay-related commands are +listed in the Imagesub:Overlay, and in the ROI +Manager window (AnalyzeToolssub:ROI-Manager...). +Appearance of overlay selections can be adjusted using ImageOverlaysub:Overlay-Options.../sub:Labels... + +As mentioned in infobox:Formats infobox:Formats, +overlays are saved in the header of tif images, and do not need to +be saved externally when using TIFF, the default file format of ImageJ. +The major advantages of overlays are summarized below: +description +[Storage of ROIs] In ImageJ it is only possible to have a single +ROI at a time. However, it is possible to add selections to the image +overlay using B (ImageOverlaysub:Add-Selection...=00005Bb=00005D). +Once added to the image overlay, ROIs can be re-activated by Alt-clicking, +Control-clicking or long-pressing ( second or longer). +Activated ROIs can be deleted by pressing the Backspace +key. Selections can also be added and recovered in bulk, using the +ImageOverlaysub:From-ROI-Manager/sub:To-ROI-Manager +commands. +[Non-destructive annotations] Overlays are the best way of annotating +images in ImageJ (fig:image-overlays). As vector graphics, +overlays do not change pixel values, can be scaled without loss of +quality even at high zoom levels (see infobox:ZoomedCanvas +infobox:ZoomedCanvas) and can be displayed at different +opacity values (see infobox:HEX infobox:HEX). +RGB snapshots of the image with embedded overlays can be created by +holding Shif F, the shortcut for ImageOverlaysub:Flatten-=00005BF=00005D. +'Flattened' images with the overlay rendered as pixel data are also +created when saving the image as PNG or JPEG (Filesub:SaveAs), +or when printing the image canvas (Filesub:Print...=00005Bp=00005D). +The Flatten command is also listed in the fig:The-ROI-Manager. +[Image ROIs] An Image selection@Image selection ImageROIImageROIimageROI +(image selection) is a ROI that displays an image as an overlay. As +described in EditSelectionsub:Image-to-Selection... +and ImageOverlaysub:Add-Image..., +this allows multiple images to be Blendblended on a single +image canvas. +description + +3D Volumessub:3D-Intro + +Currently, the support for ThreeD ROIs@3D ROIs3D ROIs3D +ROIs (selections containing contiguous cluster of voxels) is somewhat +limited in ImageJ. This limitation has been addressed by sub:ImageJ2intro +and several IJ1 plugins. The list below summarizes some of the ImageJ +plugins that deal effectively with multi-dimensional objects. Note +that a manual installation of these tools as standalone ImageJ plugins +is a challenging task given their special dependencies, reason why +they are all bundled as part of Fijisub:Fiji-intro. +figure +images/3Dviewer[3D Viewer]fig:-3D-Viewer3D Viewer (Fiji1.46o), bringing +hardware-accelerated 3D visualization to ImageJ. As explained in +sub:3D-Intro, most of plugins that truly extend ImageJ +functionally to multi-dimentional data are bundled as part of Fiji. +figure + +description +[3D Filters] Specialized ThreeD Filters@3D Filters3D Filters3D +filters such as ProcessFilterssub:Gaussian-Blur-3D... +can be installed to perform 3D operations. Examples are the http://imagejdocu.tudor.lu/doku.php?id=plugin:morphology:3d_binary_morphological_filters:start3D processing package +by Thomas BoudierIannuccelli:2010p13791 and the http://fiji.sc/wiki/index.php/3D_Binary_Filters3D binary filters +by Benjamin Schmid. +[3D Object Counter] http://imagejdocu.tudor.lu/doku.php?id=plugin:analysis:3d_object_counter:start3D Object Counter +(3D-OC) ThreeD Object Counter@3D Object Counter3D Object Countercounts +and qualifies 3D objects in a stackBolte:2006p2466, similarly +to the 2D analysis performed by Analyzesub:Analyze-Particles... +It is complemented by http://imagejdocu.tudor.lu/doku.php?id=plugin:stacks:3d_roi_manager:start3D Roi Manager +Iannuccelli:2010p13791, a companion plugin that adds a 3D +fig:The-ROI-Manager to ImageJ +[3D Viewer] http://3dviewer.neurofly.de/3D Viewer ThreeD Viewer@3D Viewer3D Viewerbrings +powerful hardware-accelerated 3D visualization to ImageJSchmid:2010p18702, +extending the limited functionality of ImageStackssub:3D-Project... +In the ImageJ fig:-3D-Viewer stacks can be displayed as +texture-based volume renderings, surfaces or orthoslices. It is macro-recordable +and can be used by other plugins as a high-level programming library +for 3D visualization +[Simple Neurite Tracer] http://fiji.sc/wiki/index.php/Simple_Neurite_TracerSimple Neurite Tracer +Simple Neurite Tracerallows semi-automated segmentation of +tubular structures in 3DLongair:2011p20768 +[TrakEM2] As mentioned earlier, misc:TrakEM2 features +powerful tools for multi-dimensional regions of interestCardona:2010p18306 +description +ImageStackssub:3D-Project.../sub:Orthogonal-Views, +Analyzesub:Surface-Plot..., infobox:Skeletonize-vs-Skeletonize3D +infobox:Skeletonize-vs-Skeletonize3D, http://fiji.sc/wiki/index.php/Special:Search?search=3d&fulltext=Search3D tools in Fiji, +http://www.longair.net/edinburgh/imagej/three-pane-crop/Three Pane Crop, +http://imagejdocu.tudor.lu/doku.php?id=tutorial:working:3d_image_processing_and_analysis_with_imagej3D image processing tutorials +on the ImageJ wikipage + + +[Settings and Preferences]Settings and Preferencessec:Settings-and-Preferences + +SettingsPreferences@Preferences Settings,Options@Options Settings,ImageJ +preferences are automatically saved in a preferences file, the +IJprefs.txt text file. This file is stored in /Library/Preferences/ +on Mac OSX, in /.imagej/ on Linux and Windows (with +referring to the user's home directory). Several macros and plugins +also write parameters to this file. If the IJprefs.txt is erased +using EditOptionssub:ResetOptions, +ImageJ will create a new one the next time it is opened resetting +all parameters to their default values. + +Sometimes, it may be useful to override (or restore) certain settings +that may have been changed during a working session. For example, +the Limit to threshold option (Analyzesub:Set-Measurements...) +will affect most measurements performed on thresholded images. Thus, +it may be wise to check the status of this parameter before each analysis, +specially when working on multiple computers. + +lstlisting[caption=Ensuring Specific Settings at Launch,label=lis:setOption,float=h,showstringspaces=false,tabsize=4] + macro "AutoRun" + setOption("DebugMode", true); + setOption("Bicubic", true); + setOption("Display Label", true); + setOption("Limit to Threshold", false); + setOption("BlackBackground", true); + run("Colors...", "foreground=white background=black"); //this line could be substituted by: setBackgroundColor(0,0,0); setForegroundColor(255,255,255); + run("Profile Plot Options...", "width=350 height=200 draw"); + run("Brightness/Contrast..."); + +lstlisting +The setOption() http://imagej.nih.gov/ij/developer/macro/functions.htmlsetOptionmacro function +can be used to set this and several other ImageJ options. Calling +this function from the StartupMacrosAutoRun"AutoRun" +macro in the StartupMacros.txt file ensures preferences are set each +time ImageJ starts. The macro lis:setOption lis:setOption +exemplifies this approach ensuring that the following settings are +enforced at startup: +enumerate +TIFF tag values are displayed by ImageJ (Debug Mode in EditOptionssub:Misc...) +Bicubic interpolation is preferred over bilinear (e.g., EditSelectionsub:Straighten...) +The name of the measured image name is recorded in the first column +of the sec:Results-Table (Display Label in Analyzesub:Set-Measurements...) +Measurements are not restricted to thresholded pixels (Limit +to Threshold in Analyzesub:Set-Measurements...) +Binary images are processed assuming white objects on a black background +(Black background in ProcessBinarysub:BinaryOptions..., +see infobox:blackBackground infobox:blackBackground) +Background color is black and foreground color is white +(EditOptionssub:Colors...) +ImageJ plots contain grid lines and are always pixels +in size (EditOptionssub:Profile-Plot-Options...) +Open the BC widget at its last saved screen position (ImageAdjustsub:Brightness/Contrast...=00005BC=00005D) +enumerate +sec:GUIcustomization, FAQsFAQFrequently Asked Questions +on http://imagejdocu.tudor.lu/doku.php?id=faq:technical:how_do_i_set_up_imagej_to_deal_with_white_particles_on_a_black_background_by_defaultImageJ wikipage, +infobox:Organizing-Commands infobox:Organizing-Commands diff --git a/plain/03-extending.txt b/plain/03-extending.txt new file mode 100644 index 0000000..786f593 --- /dev/null +++ b/plain/03-extending.txt @@ -0,0 +1,264 @@ + +Extending ImageJsec:Extending-ImageJ + +ImageJ capabilities can be extended by loadable code modules in the +form of macros, scripts or plugins. 300 macros, 500 plugins +and 20 scripts are available through the ImageJ web site. Below +is a short description of these three type of ImageJ add-ons: +lyxlistmacrosss +[sub:Macros-ExtendingIJ] The easiest way to +execute a series of ImageJ commands. The ImageJ Macrosmacro +language - a Java-like language - contains a set of control +structures, operators and built-in functions and can be used to call +built-in commands and other macros. Macro code is stored in text files +(.txt and .ijm extensions). +[sub:Plugins] Much more powerful, flexible and faster +than macros (most of ImageJ's built-in menu commands are actually +Pluginsplugins) but harder to write and debug. Plugins are +written in the JavaJava programming language (.java source +files) and compiled to .class files. +[sub:Scripts] ImageJ uses the Mozilla Rhino interpreter +to run JavaScriptJavaScripts. Similarly to plugins, scripts +have full access to all ImageJ and Java APIs but do not need to be +compiled (scripts and macros run interpretively). On the other hand, +scripts lack the simplicity of macro language and feel less integrated +in ImageJ. +lyxlist + +Macrossub:Macros-ExtendingIJ + +A Macrosmacro is a simple program that automates a series +of ImageJ commands. The easiest way to create a macro is to record +a sequence of commands using the command recorder (PluginsMacrossub:Record...). + +A macro is saved as a text file (.txt or .ijm extension) and once +installed executed by selecting the macro name in the Pluginssub:Macros +submenu, by http://imagej.nih.gov/ij/developer/macro/macros.htmlshortcutspressing a key +or, in the case of http://imagej.nih.gov/ij/developer/macro/macros.htmltoolsMacro tools, +by clicking on an icon in the ImageJ toolbar. In addition, any macro +file placed in ImageJ/plugins with an .ijm extension will be installed +in the Plugins menu like any other plugin +(before version1.41 only files with an underscore in the name would +be listed). + +There are more than 300example macros, on the ImageJ Web site. +To try one, open it in a browser window and drag it directly to the +fig:The-ImageJ-window or, copy it to the clipboard (Ctrl +A, Ctrl C), switch to IJ, and run FileNewsub:SystemClipboard=00005BV=00005D +(Ctrl Shift V), pasting the macro into a new sub:ImageJ-Macro-Editor +window. Run it using the editor's MacrosRun Macro +command (Ctrl R). Most of the example macros are also available +in the macros folder, inside the ImageJ folder. + + +Macro Programmingsub:Macro-Programming + +The ImageJ community has created excellent tutorials on macro programming. +These resources are indispensable guides to the ImageJ macro language: +enumerate +The ImageJ Macro Language - Programmer's Reference Guide +by Jrme Mutterer and Wayne Rasband. This booklet compiles most of +the documentation dispersed throughout the web related to ImageJ's +macro programming. It provides an up to date printable manual for +the ImageJ macro language: + +http://imagej.nih.gov/ij/docs/macro_reference_guide.pdf +Fourtneen new macro functionsThe Built-in Macro Functions +webpage (Helpsub:Macro-Functions... +and MacrosFunctionFinder=00005BF=00005D +in the sub:ImageJ-Macro-Editor) is the indispensable guide +to the built-in functions that can be called from the ImageJ macro +language. It is thoroughly documented and constantly updated: + +http://imagej.nih.gov/ij/developer/macro/functions.html +Tutorials on the FijiFiji webpage: + +http://fiji.sc/wiki/index.php/Introduction_into_Macro_Programming +How-tos and tutorials on the ImageJ Documentation Portal + +http://imagejdocu.tudor.lu/ +enumerate +sub:Scripts, sub:Plugins, sub:ImageJ-Macro-Editor, +sub:Fiji-Scrip-Editor + + +Scriptssub:Scripts + +JavaScriptJavaScript scripting was introduced in ImageJ1.41 +in order to bring full access to ImageJ and Java APIs (see +tab:Advantages-JavaScript). ImageJ uses the Mozilla Rhino +interpreter built into Java1.6 for Linux and Windows to run JavaScript. +Mac users, and users of earlier versions of Java, must download JavaScript.jar +into the plugins folder. This JARJARJava ARchive +file is available on the http://imagej.nih.gov/ij/download/tools/JavaScript.jarImageJ website +and is included with the Mac version of ImageJ in ImageJ/plugins/jars. + +Example JavaScript programs are available at http://imagej.nih.gov/ij/macros/js/imagej.nih.gov/ij/macros/js/. +Thread safe JavaScript code can be generated using the Recorder (PluginsMacrossub:Record...). +Scripts can be opened in the editor as any other macro. Scripts with +the extension .js can be run using MacrosRun Macro otherwise +MacrosEvaluate JavaScript (Ctrl J) must be used. + + +JavaScript Programming + +Resources on ImageJ JavaScript scripting include: +enumerate +The ImageJ web site, with growing documentation: + +http://imagej.nih.gov/ij/developer/javascript.html +Tutorials on the FijiFiji webpage: + +http://fiji.sc/wiki/index.php/Javascript_Scripting +Online scripts repository: + +http://imagej.nih.gov/ij/macros/js/ +enumerate +american +table +[Advantages and disadvantages of JavaScript]english +tab:Advantages-JavaScriptAdvantages and disadvantages +of JavaScript in ImageJ. ActionBarCodeBar A thorough +comparison between different scripting languages is available on the +http://fiji.sc/wiki/index.php/Scripting_comparisonsFiji webpage.english + + + + +minipage[t]1 +english + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/plain/04-gui.txt b/plain/04-gui.txt new file mode 100644 index 0000000..10f1544 --- /dev/null +++ b/plain/04-gui.txt @@ -0,0 +1,1059 @@ + +ImageJ User Interfacepar:User-Interface1 + +Unlike most image processing programs ImageJ does not have a main +work areaGUIGraphical User Interface. ImageJ's main +window is actually quite parsimonious containing only a menu bar (at +the top of the screen on the Mac) containing all the par:Commands, +a sub:Toolbar, a sub:Status-bar and a sub:Progress-bar. +Images, histograms, profiles, widgets, etc. are displayed in additional +windows. Measurement results are displayed in the sec:Results-Table. +Most windows can be dragged around the screen and resized. + +figure[h] +centering +[Main ImageJ window]fig:The-ImageJ-windowThe ImageJ window (version1.46j). + + +centering + +centering + +tabular>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm>p6.45mm +1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & A & B & C & D & E & F & G & H & 1321cimages/IJ_Window +10lsub:Status-bar & 11rsub:Progress-bartabular +centering + +centering + + +centering + + +tabular>m6mm>p72.5mm>p9mm>p49mm +1 & 272.5mmsub:Rectangular-Selection-Tool and sub:Round-Rectangular-Selection & 8 & sub:Wand-Tool & & 9 & sec:Text-Tool +2 & 272.5mmsub:Oval-Selection-Tool, sub:Elliptical-Selection-Tool +and sub:Brush-Selection-Tool & 10 & sec:Magnifying-Glass & & 11 & sec:Scrolling-Tool +3 & sub:Polygon-Selection-Tool & 12 & sec:Color-Picker +4 & sub:Freehand-Selection-Tool & 13 & sec:ToolSwitcher +5 & sub:Straight-Line-Selection, sub:Segmented-Line-Selection, +sub:Freehand-Line-Selection and sec:Arrow-Tool & A-H & 349mmCustomized tools installed from StartupMacros.txt, macros/toolsets/, +macros/tools/ or plugins/Tools/ +6 & sec:Angle-Tool & & +7 & sec:Point-Tool and sec:Multi-point-Tool & & tabular +figure + + + +Toolbarsub:Toolbar + +The ImageJ toolbar contains tools for making selections, drawings, +zooming and scrolling, etc. In addition, the right-side of the toolbar +contains seven slots that can host any of the http://imagej.nih.gov/ij/macros/tools/60+ tools +and http://imagej.nih.gov/ij/macros/toolsets/15+ toolsets +available on the ImageJ website (see sec:CustomToolsAndToolsets). + +All ImageJ Toolbartools share common features: +itemize +The images/tools/triangle on the bottom right +corner of some icons in the toolbar depicts a contextual menu that +can be accessed by right-clicking on the tool icon (e.g., sub:StacksMenu). +If an 'Options' dialog is available for a particular tool, it can +be accessed by double clicking on the tool icon (e.g., sub:Wand-Tool). +itemize + +Status barsub:Status-bar + +When the cursor is over an image, pixel intensities and Coordinatescoordinates +are displayed in the Status barstatus bar. After running +a filter, elapsed time and processing rate (in pixels/second) +are also displayed. When clicking on the status bar the ImageJ version, +the Java version, MemoryRAM@RAM Memory,memory +in use, memory available and percent memory used will be displayed. +As sec:Selections-Intro are created or resized, selection +properties (e.g., location, width, etc.) are displayed on the status +bar. + +In addition, clicking on ImageJ's status bar, forces the +Java garbage collector to run, which may help to reclaim unused memory +(see EditOptionssub:Memory-=000026-Threads...). +You can assess this by running PluginsUtilitiessub:Monitor-Memory...: +each click on the Status bar should lead to a spike in the ImageJ's +memory utilization. +figure[H] +images/StatusBar +figure + + +PluginsUtilitiessub:ImageJ-Properties..., +Helpsub:About-ImageJ... + + +infobox +infobox:Toggle-Cal-UnitsToggling Calibrated Units + + +If a spatial scale has been defined in Imagesub:Image>Properties... +or Analyzesub:Set-Scale..., selection +properties are displayed in the sub:Status-bar in calibrated +units. Resizing or moving while holding down Alt forces +this information to be displayed in pixels. +infobox + + + +Progress barsub:Progress-bar + +The Progress barprogress bar, located to the right of the +status bar, shows the progress of time-consuming operations. It will +not appear if the operation requires less then approximately one second. + + +tocsection + + +Toolssec:IJ-Tools + + +tocsection + + +lyxlist[1] + list + #1 + 3.5ex + -1.2ex + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/plain/05-commands.txt b/plain/05-commands.txt new file mode 100644 index 0000000..6d4cb28 --- /dev/null +++ b/plain/05-commands.txt @@ -0,0 +1,6703 @@ + +Menu Commandspar:Commands + +As described in par:User-Interface1, the menu bar lists +all ImageJ commands. It is organized in eight menus: +lyxlistwindowss +[sec:File] Basic file operations +(opening, saving, creating new images). Most are self-explanatory. +[sec:Edit] Editing and drawing operations +as well as global settings. +[sec:Image] Conversion and modification +of images including geometric transformations. +[sec:Process] Image processing, +including point operations, filters and arithmetic operations. +[sec:Analyze-Menu] Statistical measurements, +profile and histogram plotting and other operations related to image +analysis. +[sec:Plugins] Commands for creating, +editing and managing add-ons (see sec:Extending-ImageJ), +listing all the user-installed sub:Macros-ExtendingIJ, +sub:Scripts and sub:Plugins installed in the +ImageJ/plugins/ directory. +[sec:WindowMenu] Selection and management +of open windows. +[sec:Help] Updates, documentation +resources and version information. +lyxlist + +infobox +infobox:Organizing-CommandsOrganizing Commands in the Menu +Bar + + +The sec:Plugins menu can become easily cluttered after +the installation of several plugins. Since Plugins reflects +the hierarchy of directories in ImageJ/plugins/ (up to two subfolders), +submenus (i.e., subfolders) can be created to keep the menu organized, +preventing it from running off the bottom of the screen. E.g, to move +the http://imagej.nih.gov/ij/plugins/eps-writer.htmlEPS Writer +plugin into a PluginsInput-OutputPDF +submenu, one would move EPSWriter.class into ImageJ/plugins/Input-Output/PDF/. + + +In addition, checking the Move isolated plugins to Misc. menu +checkbox in EditOptionssub:Misc... +will compact the menu list by moving to PluginsMiscellaneous +all the plugins with only one command that try to install themselves +in submenus. + + +Note that external plugins can be installed in any of the ImageJ menus. +This is the case of plugins packaged in JAR files containing a configuration +file (plugins.configplugins.config) specifying the location +of the new commands implemented by the plugin. You can rename, reorganize +or move commands implemented by external plugins by editing their +plugins.config file as described on the http://rsbweb.nih.gov/ij/plugins/jar-demo.htmlJAR demo documentation page. +If you don't know in which menu a plugin has been registered, use +Show full information in the command Finder (PluginsUtilitiessub:Command-Finder) +to find out the location of the installed .jar files. + + +With sub:Fiji-intro, sub:Scripts and sub:Macros-ExtendingIJ +can be registered in any menu by saving into Fiji.app/plugins/Scripts/menu name/submenu name/. +E.g., a certain macro (.ijm file) saved in Fiji.app/plugins/Scripts/File/Import/ +is registered in the Filesub:Import submenu. + +http://fiji.sc/wiki/index.php/Description_of_ImageJ's_plugin_architectureImageJ's plugin architecture +on the Fiji website +infobox + + + +Filesec:File + + +New + +Contains commands for creating new images, stacks, hyperstacks or +text windows. + +Pluginssub:Plugins->New + + +Image [n]sub:Image...=00005Bn=00005D + +minipage[c][1][t]0.39 +images/New +minipage +minipage[c][1][t]0.61 +Creates a new image window or stack. A dialog box allows you to specify +the image title, type, dimensions and initial content. + + +Name is the title that will be used for the Window. Type +is the image type: 8-bit grayscale, 16-bit grayscale (unsigned), +32-bit (float) grayscale or RGB color. Fill With (White, +Black or Ramp) specifies how the image is initialized. +Width and Height specify the image dimensions in pixels. +Set Slices to a value greater than one to create a stack. +minipage + +ImageHyperstackssub:New-Hyperstack..., +sec:Image-Types + + +Hyperstacksub:Hyperstack... + +Alias for the ImageHyperstackssub:New-Hyperstack... +command. + + +Text Window [N]sub:TextWindow=00005BN=00005D + +Creates a new text window with the title 'Untitled.txt'. + +Pluginssub:Plugins->Newsub:Text-Window..., +sub:NewMacro, sub:Table... + + +Internal Clipboardsub:InternalClipboard + +Opens the contents of the internal ImageJ Clipboardclipboard. + +Editsub:Copy=00005Bc=00005D, sub:Cut=00005Bx=00005D, +sub:Paste-Control... + + +System Clipboard [V]sub:SystemClipboard=00005BV=00005D + +Opens the contents of the operating system Clipboardclipboard. + +Editsub:Copy-to-System, sub:Cut=00005Bx=00005D, +sub:Paste-Control... + + +Open [o]sub:Open... + +Opens an image and displays it in a separate window. Image files must +be in TIFF, GIF, JPEG, DICOM, BMP, PGM or FITS format, or in a format +supported by a reader plugin. Also opens: +itemize +ImageJ and NIH Image lookup tables (.lut extension). +Tables (in tab-delimited text format) (.xls or .csv extension, see +sec:Results-Table) +Selections (.roi or .zip extension)ZIP +Text files (.txt, .ijm, .js and .java extensions) + +itemize +Filesub:Import, sec:Image-Types, +sub:Virtual-Stacks, infobox:Open-Import infobox:Open-Import + + +infobox +infobox:Open-ImportOpening Files: FileOpen, +FileImport and Drag Drop + + +While the Filesub:Open... +command opens formats natively supported by ImageJ (images and non-images +files), the Filesub:Import submenu +provides access to plugins for additional file types (e.g., reading +'raw' files, images in ASCII format or loading images over the network). +Most of ImageJ's http://imagej.nih.gov/ij/plugins/ioInput/Output +plugins are installed on this submenu. + + +Note that almost every format known to ImageJ can be opened +by Drag & Drop@Drag Dropdragging and dropping the file +into the fig:The-ImageJ-window. E.g., in the illustration +below a remote macro file is opened by dragging its URLURLUniform Resource Locator +directly from a Web browser. + +centering + + +centering + +images/DragAndDrop +infobox + + + +Open Next [O]sub:OpenNext=00005BO=00005D + +Closes the current image and opens the next image (if any) in its +directory. Holding Alt opens the previous image (if any) in its directory. + + +Open Samplessub:OpenSamples + +Opens Sample Imagesexample images hosted on the ImageJ Web +site. These sample images are useful for creating, testing and debugging +macros since routines can be applied to the same image, regardless +of where the macro is run. Among all, probably the most used is +blobs.gif: Open SamplesBlobs (25K) [B]. + +Sample images can be downloaded from http://imagej.nih.gov/ij/images/http://imagej.nih.gov/ij/images/ +or, in bulk, from either http://imagej.nih.gov/ij/download/sample-images.zip, +or in sub:Fiji-intro, by running FileOpen SamplesCache Sample Images. +The AutoRun'AutoRun' macro in the StartupMacros.txt file +can then be used to change the default path of sample images, allowing +a complete off-line usage of the FileOpen Samples +submenu:StartupMacros + +lstlisting[caption=FijiSetting FileOpen +Samples for Offline Usage,label=lis:Offline-Samples,showstringspaces=false,tabsize=4] +/* This macro calls the Prefs.setImageURL() method to change the default path of Sample Images (http://imagej.nih.gov/ij/images/) to a local subfolder of ImageJ's directory named "samples". Note that Fiji provides this feature by default. + */ + + macro "AutoRun" + dir= getDirectory("imagej") + "samples"; + if (File.exists(dir)) + dir= replace(dir, " ", " + if (startsWith(getInfo("os.name"), "Windows")) + dir= "/"+ replace(dir, File.separator, "/"); + call("ij.Prefs.setImagesURL", "file://"+ dir +"/"); + +lstlisting + + + +Open Recent + +The submenu shows a list of the 15recently opened files. Click +on a filename to open it. + + +Importsub:Import + +This submenu lists the installed image Importreader plugins. + +sub:Non-native-Supported-Formats, http://imagej.nih.gov/ij/plugins/acqAcquisition plugins, +http://imagej.nih.gov/ij/plugins/ioInput/Output plugins, +http://imagej.nih.gov/ij/macros/VirtualStackFromList.txtVirtualStackFromList +macro, infobox:Open-Import infobox:Open-Import + + +[Image Sequence]Image Sequencesub:Image-Sequence... + +minipage[c][1][t]0.37 +images/SequenceOptions +minipage +minipage[c][1][t]0.63 +Opens a Image sequenceseries of images in a chosen folder +as a stack. Images may have different dimensions and can be of any +format supported by ImageJ (see sec:Image-Types +and HandleExtraFileTypeshttp://imagej.nih.gov/ij/plugins/file-handler.htmlHandleExtraFileTypes +plugin). Non-image files (sub:Scripts, .lut, .roi, RoiSet.zip, +etc. ) are ignored. + + + + +Information - widthheightdepth (size) - of the +stack to be created is displayed at the bottom of the dialog. +description +[Number of Images] Specifies how many images to open. +[Starting Image] If set to n, import will start +with the n image in the folder. +[Increment] If set to '2' every other image will be opened, +if set to '3' to every third image will be opened, etc.description + +minipage +description +[File Name Contains] Enter a string into this field +and ImageJ will only open files whose name contains that string. +[Enter Pattern] Regular expressions (RegexregexregexRegular expression) +can be typed here for advanced filtering (see tab:regex-syntax). +[Scale Images] Setting a value less than 100 will reduce +memory requirements. E.g., entering 50 reduces the amount of memory +needed to open a stack by 25 (two-dimensional images: +of the original data). This value is ignored if Use Virtual +Stack is checked. +[Convert to RGB] Allows a mixture of RGB and grayscale +images to be opened by converting all the sequence to RGB. Note that +if this option is unchecked and the first imported image is 8-bit +then all the remaining images in the sequence will be converted to +8-bit. Checking this option, circumvents this issue. +[Sort Names Numerically] When checked, +the stack will be opened in numeric file name order (e.g., +'name1.tif', 'name2.tif', 'name10.tif') instead of alphanumeric +order (e.g., 'name1.tif', 'name10.tif', 'name2.tif'). DICOM +files in the same series (tag0020,0011) are always sorted +by the image number (tag0020,0013). The List Stack Tags +macro, part of the http://imagej.nih.gov/ij/macros/ListDicomTags.txtListDicomTags +macro set, lists the values of the image number and image series tags. +[Use Virtual Stack] When checked, images are opened +as a read-only virtual (disk-resident) stack using a version of the +http://imagej.nih.gov/ij/plugins/virtual-opener.htmlVirtual Stack Opener +plugin. This allows image sequences too big to fit in MemoryRAM +to be opened, but access time is slower and changes are lost when +switching to a different image in the stack (see sub:Virtual-Stacks). +Note the following consequences of enabling this option: + +itemize +OverlayImage sub:Overlay-Intro are not loaded +If the folder contains tiff stacks, only the first slice of those +stacks will be imported (with RAM resident stacks, all slices are +imported and concatenated into the sequence [see ImageStacksToolssub:Concatenate...] +) +itemize +[Help] Opens http://imagej.nih.gov/ij/docs/menus/file.htmlseq1http://imagej.nih.gov/ij/docs/menus/file.htmlseq1. +description +FileSave Assub:SaveAs>Image-Seq..., +http://imagej.nih.gov/ij/macros/OpenSeriesUsingFilter.txtOpenSeriesUsingFilter +macro, Imagesub:Overlay + +table[h] +[Basic syntax of regular-expressions]tab:regex-syntaxRegular-expressions basic syntax +summary. For more information on Regexregex filtering see +http://download.oracle.com/javase/tutorial/essential/regex/. + + + +tabularclll + +2cRegex Syntax (Character Classes) & 1cExample & 1cMeaning[] & Delimit the set of characters to match & [aA] & Either lower or upper case A- & Character ranges & [0-9] & Any digit (from 0 through 9). & Any character & [0-9]. & A digit plus any other character* & Zero or more of the preceding item & .* & Any character sequence? & Zero or one of the preceding item & [0-9]? & An optional digit+ & One or more of the preceding item & [0-9]+ & At least a digit & Negation & [0-9] & Any character that is not a digit & AND (Intersection) & [0-9[3]] & A digit that is not 3 & OR (Alternation) & [0-9][a-zA-Z] & A digit or lower or upper case lettertabular +table + + + +infobox +infobox:ImportImgSeqReducing Memory Requirements When Importing +Images + + +Since ImageJ1.44d, the Filesub:Importsub:Image-Sequence... +command no longer features the Convert to 8-bit Grayscale checkbox. +This option was used to reduce memory requirements but used different +scaling for each imported image. + + +As a replacement, use the Use virtual stack option +and then convert to 8-bit using FileType8-bit. +Memory requirements can also be reduced by using the Scale Images +() option. The amount of Memorymemory allocated to ImageJ +can be adjusted in EditOptionssub:Memory-=000026-Threads... +infobox + + + +Rawsub:Import>Raw + +minipage[c][1][t]0.53 +images/ImportRaw +minipage +minipage[c][1][t]0.47 +Use this command to import images that are not in a file format directly +supported by ImageJ. You will need to know certain information about +the layout of the image file, including the size of the image, and +the offset to the beginning of the image data. + + +Interleaved RGB images have pixels stored contiguously (rgbrgbrgb) +in a single image plane. Planar RGB images have the red, green and +blue image data stored in separate 8-bit sample planes. ImageJ saves +RGB images (both TIFF and raw) in interleaved format. +minipage +description +[Image Type] There are fourteen choices depicted above. +16-bit signed integer images are converted to unsigned by +adding 32,768. 1-bit Bitmap images are converted to 8-bit. +[Image Width] The number of pixel in each row of image +data. +[Image Height] The number of rows in the image. +[Offset to First Image] The number of bytes in the +file before the first byte of image data. +[Number of Images] The number of images stored in the +file. If this value is greater than the actual number of images the +resulting stack will get truncated to the actual size. +[Gap Between Images] The number of bytes from the end +of one image to the beginning of the next. Set this value to widthheightbytes-per-pixeln +to skip n images for each image read. +[White is Zero] Should be checked if black pixels are +represented using numbers that are less than the numbers used for +white pixels. If your images look like photographic negatives, changing +this field should fix the problem. +[Little-Endian Byte Order] Probably needs to be checked +when importing 16-bit or 32-bit grayscale images from little-endian +machines such as Intel based PCs. +[Open All Files in Folder] If checked, ImageJ will +import all the images in the folder as a stack. The images must all +be the same size and type. +[Use Virtual Stack] Images are imported as virtual stacks. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/file.html#raw. +description +sec:Image-Types + + +LUTsub:Import>LUT + +Opens an ImageJ or NIH Image lookup table, or a raw lookup table. +The raw LUTLUT file must be 768bytes long and contain +256reds, 256blues and 256greens. If no image is open, a 25632 +ramp image is created to display the LUT. Note that lookup tables +with file names ending in .lut can also be opened using Filesub:Open... +or drag and drop. + + +[Text Image]Text Imagesub:Import>Text-Image + +Opens a tab-delimited text file as a 32-bit real image (see +fig:TextImages). The image's width and height are determined +by scanning the file and counting the number of words and lines. For +text files with integer values no larger than 255, use Imagesub:Type8-bit +to convert to 8-bit. Before converting, disable Scale When +Converting in EditOptionssub:Conversions... +to prevent the image from being scaled to 0-255. + +fig:TextImages, sub:PixelInspector, ImageTransformsub:ImageToResults/sub:ResultsToImage, +Save Assub:SaveAs>Text-Image..., http://imagej.nih.gov/ij/macros/OpenTextImagesAsStack.txtOpenTextImagesAsStack +macro + + +Text Filesub:Import>Text-File + +Opens a text file. Note that text files can also be opened using Filesub:Open... +or drag and drop. + + +[URL]URLsub:Import>URL + +minipage[c][1][t]0.535 +images/Url +minipage +minipage[c][1][t]0.465 +Downloads and displays known formats to ImageJ specified by a URL. +Other URLs ending with '/' or '.html' are opened in the user's +default browser. The Input URL is saved in the ImageJ preferences +file and retrieved across IJ restarts. +minipage + +It is also possible to open zip archives, using a URL, that contain +multiple DICOM images. Some example URLs are: +itemize +http://imagej.nih.gov/ij/images/ct.dcm +file:///Macintosh HD/images/Nanoprobes.tif +file:///D:imagesneuron.tif +http://imagej.nih.gov/ij/ (opens the ImageJ website) +itemize + +[Results]Resultssub:Import>Results + +Opens an ImageJ table, or any tab or CSVcomma-delimited text +file (see sec:Results-Table). Note that .csv and +.xls files can also be opened by drag and drop. + + +[Stack From List]Stack From Listsub:Stack-From-List...Stacks!From List + +Opens a stack, or virtual stack, from a text file or URL containing +a list of image file pathsC-StackFromList. The images can +be in different folders but they must all be the same size and type. +The http://imagej.nih.gov/ij/macros/VirtualStackFromList.txtVirtual Stack From List +macro demonstrates how to generate a list of images and then use that +list to open the images as a virtual stack. The http://imagej.nih.gov/ij/macros/OpenStackUsingURLs.txtOpenStackUsingURLs +macro demonstrates how to how to open an image series from a remote +server. + + +TIFF Virtual Stacksub:Import>TIFF-Virtual-Stack + +Opens a TIFF file as Stacks!Virtualvirtual stack (see +sub:Virtual-Stacks and infobox:VirtualTiff infobox:VirtualTiff). + + +[AVI]AVIsub:Import>AVI...Improved AVI support + +minipage[c][1][t]0.29 +images/AviReader +minipage +minipage[c][1][t]0.71 +Uses a built in version of the http://imagej.nih.gov/ij/plugins/avi-reader.htmlAVI reader +plugin to open an AVIAVI file (JPEG or PNG compressed, or +uncompressed) as a stack or virtual stack (one slice per video frame) +C-AviPlugins. Animation speed is retrieved from image frame +rate. AVI files can also be opened using Filesub:Open... or +drag and drop but macros must use this command to gain access to the +dialog box options. + + +ImageJ supports a restricted number of AVI formats including MJPGMJPG +(motion-JPEG) and various YUV 4:2:2/4:2:0 compressed formats (cf. http://imagej.nih.gov/ij/source/ij/plugin/AVI_Reader.javaplugin source code). +The OME Bio-Formats@OME Bio-Formats Bio-Formats,LOCI Bio-Formats@LOCI Bio-Formats Bio-Formats,Bio-formats@Bio-formats LOCI,http://loci.wisc.edu/software/bio-formatsOME Bio-Formats library +(see sub:Non-native-Supported-Formats) extends support +to MSRLE and MSV1 encoded formats. +minipage + + + + +The dialog promt allows you to choose if frames should be converted +to 8-bit grayscale or flipped vertically. For large files, an option +to open the movie as a virtual stack is also available (see +sub:Virtual-Stacks). It is also possible to specify the +starting and ending frame. Enter (zero) to specify the last frame, + to specify the second last frame, etc. + +FileSave Assub:SaveAs>Avi... + + +[XY Coordinates]XY Coordinatessub:Import>XYcoordinates...New command: FileImportXY Coordinates + +Imports a two column text file, such as those created by FileSave Assub:SaveAs>XYcoordinates..., +as a polygon selection. The selection is displayed in the current +image or, if the current image is too small, in a new blank image. +Coordinates of active selection (at evenly spaced one pixel intervals) +can be retrieved using the List coordinates options in EditSelectionsub:Properties.... + + +Close [w]sub:Close=00005Bw=00005D + +Closes the active image. + + +Close Allsub:Close-All + +minipage[c][1][t]0.48 +images/Close-All +minipage +minipage[c][1][t]0.52 +Closes all open images. An alert is displayed if there are unsaved +changes. +minipage + + +Save [s]sub:Save=00005Bs=00005D + +Saves the active image in TIFF format, the 'default' format of ImageJ +(cf. infobox:Formats infobox:Formats). To save +only a selected area, create a rectangular selection and use the Imagesub:Duplicate...=00005BD=00005D +command. Note that sub:Save=00005Bs=00005D and FileSave Assub:Tiff... +are redundant commands. + + +Save Assub:SaveAs + +Use this submenu to save the active image in TIFF, GIF, JPEG, or 'raw' +format. Can also be used to save measurement results, lookup tables, +selections, and selection XY coordinates. + + +Tiffsub:Tiff... + +Saves the active image or stack in TIFFTIFF format in redundancy +with Filesub:Save=00005Bs=00005D. +TIFF is the only format (other than 'raw') that supports all ImageJ +data types (8-bit, 16-bit, 32-bit float and RGB) and the only format +that saves spatial and density calibration. In addition sec:Selections-Intro +and sub:Overlay-Intro are also saved in the TIFF header. + +By default, 16-bit and 32-bit images are saved using big-endian +byte order. Check Save TIFF and Raw in Intel Byte Order in +the EditOptionssub:Input/Output... +dialog box to save using little-endian byte order. + +sub:Native-Formats, infobox:Formats infobox:Formats, +infobox:JpegAlert infobox:JpegAlert + + +[Gif]Gifsub:Gif... + +Saves the active image in GIFAnimationGIF format. +RGB images must first be converted to 8-bit color using using ImageType8-bit Color. +The value to be used as the transparent index (0-255) can be set +in the EditOptionssub:Input/Output... +dialog box. Stacks are saved as animated GIFs. Use ImageStacksToolssub:Animation-Options... +(or right-click on the on the play/pause icon that precedes the stack +slider) to set the frame rate. + + +Jpegsub:Jpeg... + +Saves the active image in JPEGJPEG format. Edit JPEG +Quality EditOptionssub:Input/Output... +dialog box to specify the JPEG compression level (0-100). This value +is shown on the title of the save dialog prompt. Lower values produce +smaller files but poorer quality. Larger values produce larger files +but better quality. Color sub-sampling is disabled when the value +is set to 100, reducing the likelihood of color artifacts. By default, +the DPIDPI in the JPEG header is set to 72. For a higher +value, use a unit of inch in the Analyzesub:Set-Scale... +dialog. E.g., setting Distance in Pixels to 300, Known +Distance to 1 and Unit of Length to 'inch' will set the +DPIDots Per InchDPI to 300. + +sub:Overlay-Intro are embedded when saving in Jpeg format +(see ImageOverlaysub:Flatten-=00005BF=00005D). + +infobox:Formats infobox:Formats, infobox:JpegAlert +infobox:JpegAlert + + +infobox +infobox:JpegAlertWarning on JPEG Compression + + +The JPEG format uses Lossy compressionmisc:LossyCompression +that leads to severe artifacts that are not compatible with quantitative +analyses. As such, it should only be used for http://fiji.sc/wiki/index.php/IP_PrinciplesWhy_.28lossy.29_JPEGs_should_not_be_used_in_imagingpresentation purposes +(if file size is an issue), but even then a lossless format such as +http://en.wikipedia.org/wiki/Portable_Network_GraphicsPNG +is probably more suitable. + + +The illustration below exemplifies the consequences of saving +images in a lossy format. To replicate it, open the http://imagej.nih.gov/ij/images/baboon.jpgMandrill sample image +(by drag and drop, or alternatively using FileImportsub:Import>URL +and typing the image's path, http://imagej.nih.gov/ij/images/baboon.jpg), +duplicate it (Imagesub:Duplicate...=00005BD=00005D), +save the duplicate as JPEG (FileSave Assub:Jpeg...), +run Filesub:Revert=00005Br=00005D +(so that the saved version is reloaded by ImageJ) and calculate the +difference between the two images using Processsub:Image-Calculator... + + +By adjusting the sub:Brightness/Contrast...=00005BC=00005D, +you will notice that the imperceptible JPEG artifacts are most pronounced +along regions of higher contrast changes. In addition to this edge +artifact, the JPEG algorithm may shift colors to improve compression +which may lead to artificial http://fiji.sc/wiki/index.php/Colocalization_Analysiscolocalization. +These artifacts are intrinsic to the format and may persist even if +JPEG Quality has been increased to 100 in EditOptionssub:Input/Output... +Once an image has been lossy compressed there is no way of reverting +it to the original. Given all this, and since misc:Metadata +is poorly supported in lossy formats, it is unreasonable to use JPEG +in image processing. + + +centering +tabular>p0.31>p0.31>p0.31 +Original & JPEG copy (75 quality) & Differencetabular +centering + +images/JpegArtifacts +infobox + + + +Text Imagesub:SaveAs>Text-Image... + +Saves the active image as a spreadsheet compatible tab-delimited text +file. Calibrated and floating-point images are listed with the precision +specified by Decimal places in Analyzesub:Set-Measurements... +For RGB images, each pixel is converted to grayscale using the formula + or the formula + +if Weighted RGB to Grayscale Conversion is checked in EditOptionssub:Conversions... + +fig:TextImages, sub:PixelInspector , ImageTransformsub:ImageToResults/sub:ResultsToImage, +Importsub:Import>Text-Image + +figure +images/TextImage[Text Images]fig:TextImagesText Images: FileImportsub:Import>Text-Image +and FileSave Assub:SaveAs>Text-Image... +figure + + + +Zipsub:Zip...ZIPZIP!Compressed TIFF + +Saves the active image or stack as a TIFF file inside a compressed +ZIP archive. + + +Raw Datasub:Raw-Data...Raw + +Saves the active image or stack as raw pixel data without a header. +8-bit images are saved as unsigned bytes, unsigned 16-bit images +are saved as unsigned shorts and signed 16-bit images (e.g., FileOpen SamplesCT (420K, 16-bit DICOM)) +are saved as signed shorts. 32-bit images are saved as floats and +RGB images are saved in three bytes per pixel (24-bit interleaved) +format. 16-bit and 32-bit (float) images are saved using big-endian +byte order unless Export Raw in Intel Byte Order is checked +in the EditOptionssub:Input/Output... +dialog box. + + +[Image Sequence]Image Sequencesub:SaveAs>Image-Seq... + +minipage[c][1][t]0.495 +images/SaveAsImageSequence +minipage +minipage[c][1][t]0.505 +Stacks!ExportSaves a Stack or a hyperstack as an Image sequenceimage +sequence. +description +[Format] Specifies the output format that can be +set to either BMP, FITS, GIF, JPEG, PGM, PNG, Raw, Text Image, +TIFF, or Zip (cf. sec:Image-Types). In IJ1.44 +and later, sub:Overlay-Intro are embedded when saving in +JPEG or PNG format. +[Name] Specifies the leading string that will be common +to all numeric filenames.description + +minipage +description +[Start At] (Stacks only) Specifies the starting number +of the sequence. +[Digits (1-8)] The number digits of the incremental sequence. +Filenames are padded with leading zeroes. +[Use slice labels as filenames] (Stacks +only) If checked, each slice will be saved with its own label (the +image subtitle displayed above the image, see sub:Remove-Slice-Labels) +and no numeric sequence will be used. +description +With hyperstacks, images are saved using 'Nametdzdcd' +in which d is the incremental number of specified Digits; +t, the frame; z, the slice and c, the channel, so e.g., +for the depicted snapshot the first image would be saved as 'mitosist001z001c001.tif'. + + +AVIsub:SaveAs>Avi... + +minipage[c][1][t]0.47 +images/SaveAsAvi +minipage +minipage[c][1][t]0.53 +Stacks!ExportExports a stack or hyperstack as an AVIAVI +fileC-AviPlugins. Note that AVI files larger than 2GB +are not correctly written. +description +[Compression] JPEG, PNG or Uncompressed. +With IJ1.44 and later, sub:Overlay-Intro are embedded +when saving in JPEG or PNG format. The default compression is JPEG. description + +minipage +description +[Frame] Specifies the frame frequency. The proposed value is read +from ImageStacksToolssub:Animation-Options... +and Imagesub:Image>Properties..., as long as +the unit of Frame Interval is 'sec'. +description +FileImportsub:Import>AVI... + + +PNGsub:PNG... + +Saves the active image in PNGPNG (Portable Network Graphics) +format. All image types, except RGB, are saved as 8-bit PNGs. 16-bit +images are saved as 16-bit PNGs. With 8-bit images, the value to +be used as the transparent index (0-255, -1 for "none") +can be set in the EditOptionssub:Input/Output... +dialog box. sub:Overlay-Intro are embedded when saving +in PNG format. + + +FITSsub:FITS... + +Saves the active image in FITSFITS (Flexible Image Transport +System) formatC-FITSwriter. + + +LUTsub:LUT... + +Saves the active image's LUTlookup table to a file. The 768byte +file consists of 256red values, 256green values and 256blue +values. + + +Resultssub:Measurements... + +Exports the contents of the 'Results' window as a tab-delimited +or CSVcomma-delimited (.csv) text file. Prior to ImageJ1.44b +this command used to be named 'Measurements'. + + +Selectionsub:Selection... + +Saves the current area selection boundary to a file, that can be later +retrieved using Filesub:Open... to restore the +selection. Active sec:Selections-Intro and sub:Overlay-Intro +are saved in the TIFF header by default (see FileSave Assub:Tiff...). + + +[XY Coordinates]XY Coordinatessub:SaveAs>XYcoordinates... + +Exports the XY coordinates of the active ROI as a two column, tab-delimited +text file. ROI Coordinatescoordinates can also be retrieved +using the List coordinates option in EditSelectionsub:Properties..., +that tabulates ROI coordinates at evenly spaced one pixel intervals. + +sub:Sub-pixel-Selections, FileImportsub:Import>XYcoordinates... + + +Revert [r]sub:Revert=00005Br=00005D + +RevertUndoReloads the active image, stack or hyperstack +from disk, reverting it to its last saved state. It is actually a +shortcut for closing the window without saving, and then reopening +it. Note that it may not work with sub:Non-native-Supported-Formats +opened through external plugins such as the Bio-Formatshttp://loci.wisc.edu/software/bio-formatsOME Bio-Formats library. + +sec:Undo-and-Redo + + +Page Setupsub:Page-Setup... + +minipage[c][1][t]0.305 +images/PageSetup +minipage +minipage[c][1][t]0.695 +The Page Setup dialog allows you to control the size of printed output, +plus other Printprinting options: +description +[Scale] Values less than 100 reduce the size of printed +images and values greater than 100 increase the size. 100 corresponds +to 72 pixels per inch (ppiPPIppiPixels per inch), +about the unzoomed screen size of the image. The size of the printed +image is determined by the Scale value and the width and height +of the image in pixels. Spatial calibration is ignored.description + +minipage +description +[Draw border] If checked, ImageJ will print a one pixel +wide black border around the image. +[Center on page] If checked, the image will be printed +in the center of the page instead of in the upper left corner. +[Print title] If checked, the title of the image will +be printed at the top of the page. +[Selection only] If checked, current selection will be +printed instead of the entire image. +[Rotate 90] If checked, +the image will be rotated 90 to the left before being printed. +[Print actual size] Considers the DPI information in +the image header (typically 72, cf. sub:Jpeg...). For +a higher value, use a unit of inch in the Analyzesub:Set-Scale... +dialog. E.g., setting Distance in Pixels to 300, Known +Distance to 1 and Unit of Length to 'inch' will set the +DPIDPI to 300. +description + +Print [p]sub:Print...=00005Bp=00005D + +PrintPrints the active image. The size of the printed image +will normally be slightly less its size on the screen (unzoomed). +Use the sub:Page-Setup... dialog to increase of decrease +the size of printed images. Images larger than the page are scaled +to fit. sub:Overlay-Intro are embedded when printing images. + + +Quit + +Prompts you to save all unsaved images and then exits. You can also +Quitexit ImageJ by clicking on the close button in its window's +title bar. + + + + +Editsec:Edit + + +Undo [z]sub:Undo-=00005Bz=00005D + +Described in sec:Undo-and-Redo. + + +Cut [x]sub:Cut=00005Bx=00005D + +Copies the contents of the current image selection to the internal +clipboard, filling the selection with the current background color. + +Editsub:Copy-to-System, sub:Paste-Control... + + +Copy [c]sub:Copy=00005Bc=00005D + +Copies the contents of the current image selection to the internal +clipboard. If there is no selection, copies the entire active image. +The amount of image data copied is shown in the status bar. + +Filesub:InternalClipboard, sub:Paste-Control... + + +Copy to Systemsub:Copy-to-System + +Copies the contents of the current image selection to the system Clipboardclipboard. + +FileNewsub:SystemClipboard=00005BV=00005D, +sub:Copy=00005Bc=00005D, sub:Paste-Control... + + +Paste [v]sub:Paste=00005Bv=00005D + +Inserts the contents of the internal clipboard (or from the system +clipboard if the internal clipboard is empty) into the active image. +The pasted image is automatically selected, allowing it to be dragged +with the mouse. Click outside the selection to terminate the paste. +Select Editsub:Undo-=00005Bz=00005D to abort +the Pastepaste operation. + +sub:Paste-Control... + + +Paste Controlsub:Paste-Control... + +minipage[c][1][t]0.405 +images/PasteControl +minipage +minipage[c][1][t]0.595 +After pasting, use the PastePaste Control pop-up menu to +control how the image currently being pasted is transferred to the +destination image. + + +Except for Blend and Transparent, the Paste Control transfer modes +are the same as those listed in the description of Processsub:Image-Calculator... +The Blend mode is the same as the Image Calculator Average mode. In +Transparent mode, white/black pixels are transparent and all other +pixels are copied unchanged. + +ImageOverlay sub:Add-Image... +minipage + + +Clearsub:Clear + +Erases the contents of the selection to the current background color. +Backspace and Del keys are shortcuts to this command. With stacks, +a dialog is displayed offering the option to clear the selection in +all stack images. Clear by pressing Backspace to avoid this dialog. + +sub:Clear-Outside, sub:Fill-=00005Bf=00005D, +sec:Color-Picker + + +Clear Outsidesub:Clear-Outside + +Erases the area outside the current image selection to the background +color. + +sub:Clear, sub:Fill-=00005Bf=00005D, sec:Color-Picker + + +Fill [f]sub:Fill-=00005Bf=00005D + +Fills the current selection with the current foreground color. With +stacks, a dialog is displayed offering the option to fill the selection +in all stack images. Fill the selection by pressing F to avoid this +dialog. + +sub:Clear, sub:Draw-=00005Bd=00005D, sec:Color-Picker + + +Draw [d]sub:Draw-=00005Bd=00005D + +Outlines the current selection using the current foreground color +and line width. The foreground and background colors can also be set +using the EditOptionssub:Colors... +command. Use the EditOptionssub:Line-Width... +command, or double click on the line tool, to change the line width. + +With stacks, a dialog is displayed offering the option to draw the +selection in all stack images. Draw the selection by pressing D to +avoid this dialog. + +Analyzesub:Label, sec:Color-Picker, +infobox:Color infobox:Color, infobox:Wider-Lines +infobox:Wider-Lines + +center +infobox +infobox:Wider-LinesDrawing Lines Wider Than One-Pixel + + +If the line width is an even number, the selection boundary +is at the center of the line. If the line width is odd (1, 3, ), +the center of the line drawn is displaced from the selection edge +by pixel to the bottom right. Thus the line center +(the line in case of ) is inside the selection at +the top and left borders, but outside at the bottom and right borders. +Rectangular selections (but not polygonal selections or traced selections +that happen to be rectangular) are an exception to this rule: For +rectangular selections, one-pixel wide outlines are always drawn +inside the rectangle. Thicker lines are drawn as for the other selection +types. +infobox + +center + + +Invert [I]sub:Invert-=00005BI=00005D + +Creates a reversed image, similar to a photographic negative, of the +entire image or selection. For 8-bit and RGB images (see sec:Image-Types), +Invert always uses and , regardless of the data +values. For 16-bit and 32-bit images, the actual minimum and maximum +are used (rather than the full range of the pixel type). + +ImageLookup Tablessub:Invert-LUT + + +[Selection]Selectionsub:SelectionSubMenuUndo support extended to EditSelection commands + +figure[h] +spacing0.69999999999999996 + +tabular>m0.074>m0.074>m0.072>m0.072>m0.072>m0.072>m0.074>m0.072>m0.072>m0.082 +Original & sub:Fit-Spline & sub:Fit-Circle & sub:Fit-Ellipse & sub:Convex-Hull & sub:Make-Inverse & sub:Create-Mask & sub:Area-to-Line & sub:Make-Band... & sub:To-Bounding-Boxtabular + +images/SelectionFits + +[ROI manipulations]fig:ROI-manipulationsROI manipulations using Editsub:SelectionSubMenu +commands. General handling of ROIs and sub:Overlay-Intro +is described in sec:Selections-Intro. +spacing +figure + + + +Select All [a]sub:Select-All-=00005Ba=00005D + +Creates a rectangular selection that is the same size as the image. + + +Select None [A]sub:Select-None-=00005BA=00005D + +Deactivates the selection in the active image. + + +Restore Selection [E]sub:Restore-Selection-=00005BE=00005D + +Restores the previous selection to its original position. A selection +is saved when you:Selection!Restore +itemize +Delete the selection by clicking outside of it +Draw a new selection +De-activate the image containing the selection +Close the image containing the selection +Use a command that deletes or modifies the selection +itemize +AnalyzeToolssub:ROI-Manager... + +infobox +infobox:TransferSelectionsTransferring Selections Between +Images + + +You can transfer a selection from one image to another by +activating the image with the selection, activating the destination +image, then pressing ShiftE (the keyboard shortcut +for EditSelectionsub:Restore-Selection-=00005BE=00005D). +This shortcut can also be used to restore accidentally deleted ROIs. +Alternative ways to transfer ROIs across images involve the fig:The-ROI-Manager +and the cursor synchronization features provided by AnalyzeToolssub:SynchronizeWindows. +infobox + + + +[Fit Spline]Fit Splinesub:Fit-Spline + +Fits a Fit!Cubic splinecubic spline curve to a polygon or +polyline selection (see fig:ROI-manipulations). + +sub:Straighten..., sub:Interpolate + + +Fit Circlesub:Fit-Circle + +Fits a Fit!CircleAlgorithm!Newton-based Pratt fit@Newton-based Pratt fitcircle +to a multipoint (with at least 3 points) or area selectionC-FitCircle +(see fig:ROI-manipulations). Composite selections +are not supported. With open shapes (lines and points), the fitting +algorithm (Newton-based Pratt fit) described in Pratt V, "Direct +least-squares fitting of algebraic surfaces", Computer Graphics, +Vol. 21, pp 145-152 (1987) is used. With closed shapes, the command +creates a circle with the same area and centroid of the selection. + + +[Fit Ellipse]Fit Ellipsesub:Fit-Ellipse + +Replaces an area selection with the best Fit!Ellipsefit ellipse +(see fig:ROI-manipulations). The ellipse will have +the same area, orientation and centroid as the original selection. +The same fitting algorithm is used to measure the major and minor +axis lengths and angle when Fit Ellipse is selected in Analyzesub:Set-Measurements... + +http://imagej.nih.gov/ij/macros/DrawEllipse.txtDrawEllipse +macro + + +[Interpolate]Interpolatesub:InterpolateNew command: EditSelectionInterpolate + +minipage[c][1][t]0.265 +images/Interpolate +minipage +minipage[c][1][t]0.735 +Sub-pixel selectionsFloating point coordinates@Floating point coordinates Sub-pixel selections,Converts +the active selection into a sub-pixel resolution ROI of floating-point +coordinates spaced interval pixels apart. If Smooth +is checked, traced and freehand selections (see sec:Area-selection-tools) +are first smoothed using a 3-point running average. Refer to sub:Sub-pixel-Selections +for more details. +minipage + +fig:Subpixel-selections, sub:Fit-Spline, EditOptionssub:Profile-Plot-Options... + + +Convex Hullsub:Convex-Hull + +Replaces a polygon of freehand selection with its Convex hullconvex +hull (see fig:ROI-manipulations), determined by +the Algorithm!Gift wrapGift wrap algorithm@Gift wrap algorithm Convex hull,http://en.wikipedia.org/wiki/Gift_wrapping_algorithmgift wrap algorithm. +The convex hull can be thought of as a rubber band wrapped tightly +around the points that define the selection. + +sub:Fit-Ellipse, http://imagej.nih.gov/ij/macros/ConvexitySolidarity.txtConvexitySolidarity +macro, http://www.dentistry.bham.ac.uk/landinig/software/software.htmlConvexHullPlus +plugin + + +Make Inversesub:Make-Inverse + +Creates an inverse selection (see fig:ROI-manipulations). +What is 'inside' the selection will be 'outside', and vice versa. + + +Create Masksub:Create-Mask + +Creates a new 8-bit image called Mask'Mask' whose pixels +have a value of 255 inside the selection and 0 outside (see +fig:ROI-manipulations). By default, this image has an inverting +LUT, so black is 255 and white is 0 unless Black Background +in ProcessBinarysub:BinaryOptions... +is checked. + +ProcessBinarysub:Convert-to-Mask, +infobox:InvertedLutMask infobox:InvertedLutMask, +infobox:blackBackground infobox:blackBackground + + +Create Selectionsub:Create-Selection + +Creates a selection from a thresholded image or a binary maskC-CreateSelection. + + +[Properties [y]]Properties [y]sub:Properties...Selection!Properties + +minipage[c][1][t]0.365 +images/Properties +minipage +minipage[c][1][t]0.635 +Opens a dialog box that allows the user to assign a contour color +(Stroke color) and a contour width (Width) to the active +selection or a filling color. Note that selections can be either filled +or contoured, but not both. The default selection colors (black, +blue, cyan, green, magenta, orange, +red, white, yellow) can be typed textually. Any +other color must be typed using hex notation (see infobox:HEX +infobox:HEX). + + +Set Stroke width to 0 to have selections drawn using a width +of one pixel regardless of the image magnification (see infobox:ZoomedCanvas +infobox:ZoomedCanvas). +minipage + +With sec:Text-Tool selections, it is also possible to specify +the font size and text alignment. Choose List coordinates to +retrieve a dedicated table of XY coordinates from the active selection +at evenly spaced one pixel intervals. + +Note that while this command can only be applied to the active selection, +the ROI Manager's Properties command (AnalyzeToolssub:ROI-Manager...) +can be applied to multiple ROIs. + +sec:Selections-Intro, ImageOverlaysub:Add-Selection...=00005Bb=00005D, +FileImportsub:Import>XYcoordinates..., +FileSave Assub:SaveAs>XYcoordinates... + + +[Rotate]Rotatesub:Rotate... + +minipage[c][1][t]0.315 +images/RotateSelection +minipage +minipage[c][1][t]0.685 +TransformRotates the selection (using floating-point coordinates) +by the specified number of degrees. A negative number indicates counter-clockwise +rotation. This command runs the http://imagej.nih.gov/ij/source/macros/RotateSelection.txtRotateSelection +macro in ij.jar. + +http://imagej.nih.gov/ij/macros/FlipSelection.txtFlipSelection +macro +minipage + + +Enlargesub:Enlarge... + +minipage[c][1][t]0.325 +images/EnlargeSelection +minipage +minipage[c][1][t]0.675 +TransformGrows an area selection by a specified number of +pixels. Enter a negative value to shrink the selection. This command +runs the http://imagej.nih.gov/ij/source/macros/EnlargeSelection.txtEnlargeSelection +macro in ij.jar. http://imagej.nih.gov/ij/macros/ShrinkSelection.txtShrinkSelection +is a variation of this macro that does not shrink polygonal selections +from the edges of the image. +minipage + +infobox +infobox:CompositesConverting Composite Selections + + +Enter zero in the EditSelectionsub:Enlarge... +dialog box to convert Selection!Compositesub:Composite-selections +into polygon selections. Note, however, that the conversion may fail +if the composite ROI is composed of more than one piece and/or contains +internal holes. +infobox + + + +[Make Band]Make Bandsub:Make-Band... + +minipage[c][1][t]0.28 +images/MakeBand +minipage +minipage[c][1][t]0.72 +Takes an area selection and creates a band with a thickness of the +specified number of pixels (see fig:ROI-manipulations). +If you imagine the band as a doughnut shape, then the original selection +corresponds to the hole (i.e. the band is made by growing out the +original selection). + +http://imagej.nih.gov/ij/source/macros/MakeSelectionBand.txtMakeSelectionBand, +the macro that implemented this command in previous IJ versions. +minipage + + +Specifysub:Specify... + +minipage[c][1][t]0.27 +images/Specify +minipage +minipage[c][1][t]0.73 +Opens a dialog that allows the user to define a rectangular or elliptical +selection. Width and Height are the dimensions of the +selection. X Coordinate and Y Coordinate define the +position of the selection. Check Oval to create an elliptical +selection. If Centered is checked, the selection is positioned +so X Coordinate and Y Coordinate define the center of +the selection, otherwise they define the upper left corner. + + +This command is also available through the ROI Manager More +drop-down menu (see AnalyzeToolssub:ROI-Manager...). +minipage + + +Straightensub:Straighten... + +This command Straightenstraightens a curved object in an +image (see fig:Straighten). Fit!Cubic splineThe +curved object must first be outlined using the sub:Segmented-Line-Selection. +Double click on the line tool icon to open the ImageAdjustsub:Line-WidthSlider +widget, in order to adjust the width of the line selection. By default, +the Straighten command fits a cubic spline curve to the points +that define the line, so it is not necessary to check the Spline +Fit checkbox. Note that Straighten also works with straight +line selections. In this case, the object defined by the line selection +is rotated to be horizontal. +figure[h] +images/Straighten[Straightening filamentous objects]fig:StraightenEditSelectionsub:Straighten.... +As described in sub:Segmented-Line-Selection, the points +of a polyline selection can be repositioned (dragged), deleted (using +Alt-click) or duplicated (using Shift-click). Press Shift E (EditSelectionsub:Restore-Selection-=00005BE=00005D) +to restore accidentally deleted lines. +figure + + +http://imagej.nih.gov/ij/plugins/straighten.htmlStraighten plugin, +Imagesub:Transform + + +To Bounding Boxsub:To-Bounding-BoxBounding box + +Converts a non-rectangular selection to the smallest rectangle that +completely contains it. + + +[Line to Area]Line to Areasub:Line-to-AreaEditSelectionLine to Area now works with one pixel wide straight lines + +Converts a line selection to an area (traced) ROI. + + +[Area to Line]Area to Linesub:Area-to-Line + +Converts a non-composite area selection to its enclosing outline (see +fig:ROI-manipulations). The obtained line will have the +width specified in the ImageAdjustsub:Line-WidthSlider +widget. Note that by design Area to Line does not create closed paths. +E.g., the converted outline of a rectangular selection will be composed +of only three segments, with the first and fourth corner points of +the rectangle being disconnected. + +sub:Composite-selections, sub:Line-to-Area + + +[Image to Selection]Image to Selectionsub:Image-to-Selection...New command: EditSelectionImage to Selection + +minipage[c][1][t]0.35 +images/ImageToSelection +minipage +minipage[c][1][t]0.65 +Creates an image selection Annotation!Layers@Layers ImageROI, Overlay,ImageROI(ImageROI). +Image selections are sub:Overlay-Intro that can be moved +around the canvas (see ImageOverlaysub:Add-Image...). +Once created, opacity of the blended image can be re-adjusted at any +time using EditSelectionsub:Properties.... +Use Shift E (EditSelectionsub:Restore-Selection-=00005BE=00005D) +to recover the blending image after clicking outside its limits. Use +Shift F (sub:Flatten-=00005BF=00005D) to finally embed +the imageROI. +minipage + +Note that image selections behave only partially as regular selections +(e.g., can be added to the ROI Manager list, can be moved beyond image +boundaries but cannot be resized or rotated). However they are stored +in the TIFF header and can be saved and restored when saving images +in TIFF format. + +sub:Paste-Control...(Blend transfer mode), ImageStacksToolspar:Insert..., +sub:ROI-Manager... + + +[Add to Manager [t]]Add to Manager [t]sub:Add-to-Manager + +Adds the current selection to the ROI Manager (AnalyzeToolssub:ROI-Manager...). +If there is no selection the ROI Manager is opened. + + +Optionssub:Options + +Use commands in this submenu to change various ImageJ user preference +SettingsPreferences@Preferences Settings,Options@Options Settings,settings. + + +Line Widthsub:Line-Width... + +minipage[c][1][t]0.26 +images/LineWidth1 +minipage +minipage[c][1][t]0.74 +Displays a dialog box that allows to change the line width (in pixels) +of line selections (see sec:Line-Selection-Tools) +and concomitantly the lines generated by the Editsub:Draw-=00005Bd=00005D +command. This legacy command has been superseded by the ImageAdjustsub:Line-WidthSlider +widget, but required since the latter is not recordable (see +PluginsMacrossub:Record...). +minipage + + +[Input/Output]Input/Outputsub:Input/Output... + +minipage[c][1][t]0.412 +images/InputOutput +minipage +minipage[c][1][t]0.588 +description +[JPEG quality (0-100)] JPEG!QualitySpecifies +the compression level used by FileSave Assub:Jpeg... +Requesting a higher degree of compression (a lower value) will result +in smaller files, but poorer image quality. Note that lossy JPEG compression +creates serious artifacts, see infobox:Formats infobox:Formats. +[GIF and PNG transparent index] GIF!TransparencyPNG!TransparencySpecifies +the transparent color used for images saved in GIF and PNG formats. +Use -1 for "none". Note that PNG and GIF transparency only works +with 8-bit images.description + +minipage +description +[File extension for tables] Sets +the default extension to be used when saving sec:Results-Tables. +Files with .txt and .xls extensions are saved in tab-delimited format +and files with .csv extensions are saved in comma-delimited format. +[Use JFileChooser to open/save] Enables +versions of FileOpen and FileSave As that +use the JavaJava SwingSwing's JFileChooserJFileChooser +instead of the native OS dialogs. The main advantage of JFileChooser +is the ability to open multiple files by Shift-clicking to select +multiple contiguous files and control-clicking to select more than +one individual file. On the other hand, it is slower, uses more memory, +and does not behave like the file open and save dialogs used in other +applications. It requires Java 2, which is included with the Linux +and Windows distributions of ImageJ and is built into Mac OSX. +[Save TIFF and raw in intel byte order] Specifies +the byte order used when saving 16-bit and 32-bit images using FileSave Assub:Raw-Data..., +or FileSave Assub:SaveAs>Image-Seq... +when Raw is chosen as the format. Check this option to export +images using the order used by Intel 86 based processors +(little-endian). This http://en.wikipedia.org/wiki/EndiannesWikipedia article +has more information. +[Results Table Options] Specifies if +column headers and row numbers should be saved or copied +from ImageJ tables such as the Results and Summarize +windows (see sec:Results-Table). +description + +Fontssub:Fonts... + +Opens a small widget with three pop-up menus for specifying the typeface, +size, style and antialiasing (Smooth checkbox) of the font +used by the sec:Text-Tool and ImageStackssub:Label... +It is also possible to adjust the horizontal text alignment using +the style drop-down menu: Left (the default), Right, +or Centered. The widget is more easily opened by double clicking +on the sec:Text-Tool. + +center +images/Fonts +center + + +[Profile Plot Options]Profile Plot Optionssub:Profile-Plot-Options...Plot profile + +Use this dialog to control how Graphplots generated by ImageJ +are displayed (ImageStackssub:Plot-Z-axis-Profile..., +Analyzesub:Plot-Profile-=00005Bk=00005D, Analyzesub:Calibrate..., +AnalyzeToolssub:Curve-Fitting..., +Multi Plot [AnalyzeToolssub:ROI-Manager...], +etc.). +description +[Plot Width and Plot Height] Specify +the length (in pixels) of the X-axis (Plot Width) and Y-axis +(Plot Height). +description +minipage[c][1][t]0.335 +images/ProfilePlotOptions +minipage +minipage[c][1][t]0.665 +description +[Fixed y-axis Scale] If checked, the Y-axis range is +fixed and the specified Minimum Y +and Maximum Y values are +used, otherwise, plots are scaled based on the minimum and maximum +gray values. +[Do not Save x-values] If checked, 'List', +'Save' and 'Copy' buttons will +appear in profile plot windows. +[Auto-close] If checked, profile plot windows will be automatically +closed when 'List', 'Save' and 'Copy' are clicked on. +[Vertical Profile] If checked, row average plots +of rectangular areas (or line selections wider than 1 pixel) will +be generated instead of the default column average plots. Note that +evoking sub:Plot-Profile-=00005Bk=00005D with Alt B will +generate vertical profiles. description + +minipage +description +[List values] If checked, the list of values will +be automatically opened. If Auto-close is also checked, the +plot is closed and only the list of values remains open. +[Interpolate line profiles] If checked, +Analyzesub:Plot-Profile-=00005Bk=00005D will +use Bilinear interpolationbilinear Interpolationinterpolation +to retrieve intensity values along non-straight line selections. +[Draw grid lines] If checked, gray grid lines will be +drawn in the plot. +[Sub-pixel resolution] If checked, line selections +created on zoomed images will use Sub-pixel accuracyfloating-point +coordinates, resulting in smoother curves (see sub:Sub-pixel-Selections +and EditSelectionsub:Interpolate). +[Help] Opens http://imagej.nih.gov/ij/docs/menus/edit.htmlplot-optionshttp://imagej.nih.gov/ij/docs/menus/edit.htmlplot-options. +description + +[Rounded Rect Tool]Rounded Rect Tool + +See sub:Round-Rectangular-Selection. + + +Arrow Tool + +See sec:Arrow-Tool. + + +Point Toolsub:Point-Tool... + +See sec:Point-Tool. + + +Wand Toolsub:Wand-Tool... + +See sub:Wand-Tool. + + +Colorssub:Colors...Color!Settings + +minipage[c][1][t]0.325 +images/Colors +minipage +minipage[c][1][t]0.675 +Displays a dialog box that allows you to set Foreground, Background +and Selection color. As mentioned earlier, the selection color +is highlighted in the sec:Point-Tool and sub:Wand-Tool +icons. Drawing colors are displayed in the sec:Color-Picker +(foreground and background colors) and drawing tools such as the sub:ArrowTool2, +sub:Brush, sub:FloodFiller and sub:Pencil +(foreground color only). +minipage + +ImageColorsub:Color-Picker...=00005BK=00005D, +lis:ChangeSelectionColor + +lstlisting[caption=Using a Keyboard Shortcut to Change +Selection Color,label=lis:ChangeSelectionColor,showstringspaces=false,tabsize=4] + /* This macro loops through the all the possible Selection colors using "q" as a keyboard shortcut */ + var cIdx; + macro "Change Selection Color [q]" + color= newArray("red", "green", "blue","magenta", "cyan", "yellow", "orange", "black", "white"); + run("Colors...", "selection="+ color[cIdx++]); + if (cIdx==color.length) cIdx= 0; + +lstlisting + + + +[Appearance]Appearancesub:Appearance...AppearanceSettings + +minipage[c][1][t]0.343 +images/Appearance +minipage +minipage[c][1][t]0.657 +This dialog contains options that control how images are displayed, +an option to display better looking toolbar icons, and an option to +set the menu font size. +description +[Interpolate zoomed images] Uses interpolation instead +of pixel replication when displaying zoomed images. +[Open Images at 100] Newly +open images are displayed using 100 magnification (1image pixel += 1screen pixel).description + +minipage +description +[Black Canvas] Causes the image canvas (white by default) +to be rendered in black. This is useful when looking at X-ray images +in order to avoid high contrasting intensities at the image edges. +[No image border] Displays images without +the default one pixel wide black border. +[Use inverting lookup table] Causes +newly opened 8-bit images to have inverted pixel values, where white +and black. This is done by both inverting the pixel values +and inverting the LUT. Use the ImageLookup Tablessub:Invert-LUT +command to invert an image without changing the pixel values. +[Double Buffer Selections] Reduces flicker when working +with complex selections but it also increases memory usage and slows +screen updates. It is not needed on Mac OSX, which has built in +double buffering. +[Antialiased tool icons] Smooths and darken the +tool icons in the fig:The-ImageJ-window. This option is +enabled by default on all operating systems. On Windows XP, enable +Clear Type sub-pixel anti-aliasing to improve the quality of text +in menus. +[Menu font size] Specifies the size of the ImageJ window +menu font. Use a size of 0 (zero) to use Java's default menu font +size. Changing the font size requires the restarting of ImageJ. This +option is ignored on Mac OSX. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/edit.html#appearance. +description +sec:GUIcustomization + + +Conversionssub:Conversions...Conversions + +minipage[c][1][t]0.47 +images/Conversions +minipage +minipage[c][1][t]0.53 +Use this dialog to set options that control how images are converted +from one type to another. +minipage +description +[Scale When Converting] ImageJ will scale +from min-max to 0-255 when converting from 16-bit or 32-bit to +8-bit or to scale from min-max to 0-65535 when converting from +32-bit to 16-bit. Note that Scale When Converting is always +checked after ImageJ is restarted. +[Weighted RGB Conversions (0.30,0.59,0.11)] When +checked, the formula +is used to convert RGB images to grayscale. If it is not checked, +the formula +is used. The default weighting factors (0.299,0.587,0.114), +which are based on human perception, are the ones used to convert +from RGB to YUV, the color encoding system used for analog television. +The weighting factors can be modified using the http://imagej.nih.gov/ij/developer/macro/functions.htmlsetRGBWeightssetRGBWeights() +macro function. +description +sec:Image-Types, infobox:Color + + +Memory Threadssub:Memory-=000026-Threads... + +minipage[c][1][t]0.42 +images/MemoryAndThreads +minipage +minipage[c][1][t]0.58 +Use this dialog to specify the maximum amount of Memorymemory +available to ImageJ and the number of threads used by filters when +processing stacks. + JavaJava applications such as ImageJ will only use the memory +allocated to them (typically 640MB) but this dialog allows the +user to allocate more than the default. +minipage + + +Note that specifying more than 75 of real RAM@RAM Memory,RAM +could result in virtual RAM being used, which may cause ImageJ to +become slow and unstable. Also note that this dialog cannot be used +to set the memory allocation if ImageJ is run from the command line +or by double clicking on ij.jar. +description +[Maximum memory] sixty four-bit@64-bit64-bit +OS and a 64-bit version of JavaJava are required to use +more than 1700MB of memory. Windows users must be running +a 64-bit version of Windows and must install a 64-bit version of +Java. Mac users must be running OS X 10.5 or later and may need to +use the Java Preferences utility (in /Applications/Utilities/Java) +to select a 64-bit version of Java. They may also need to switch +to the ImageJ64 application. Linux users need to be running 64-bit +versions of Linux and Java. The title of the MemoryThreads +dialog box changes to Memory(64-bit) when ImageJ +is running on a properly configured 64-bit system. +[Parallel threads for stacks] Determines +the number of parallel threads used by commands in the Processsub:Filters +and the Processsub:Math submenus when processing +stacks. The default value is the number of available processors. +[Keep multiple undo buffers] If checked, the Undoundo +buffer will be preserved when switching images. Editsub:Undo-=00005Bz=00005D +remains restricted to the most recent operation, but is available +for each opened image, as long as the buffer allows it. If Keep multiple undo buffers +is unchecked, the undo buffer is reset every time the active (frontmost) +image changes. +[Run garbage collector on status bar click] If +checked, forces the Java garbage collector to run every time the user +clicks on the sub:Status-bar, which may help to reclaim +unused memory (see also PluginsUtilitiessub:Monitor-Memory...). +[Help] Opens http://imagej.nih.gov/ij/docs/menus/edit.html#memory. +description +http://imagejdocu.tudor.lu/doku.php?id=faq:technical:how_do_i_increase_the_memory_in_imagejFAQs on the ImageJ wikipage + + +[Proxy Settings]Proxy Settingssub:Proxy-Settings... + +minipage[c][1][t]0.375 +images/ProxySettings +minipage +minipage[c][1][t]0.625 +Use this dialog to modify the Proxy serverhttp://en.wikipedia.org/wiki/Proxy_serverproxy +settings of the Java Virtual Machine. This may be required for ImageJ +to connect to the internet in certain machines running behind HTTP +proxies. For example, proxy settings may be required to update ImageJ +using the Helpsub:Update-ImageJ... command or +to open the images in the Filesub:OpenSamples +submenu. +minipage + +To use the system proxy settings enable the Or use system proxy settings +option (this will set the java.net.useSystemProxies property +to true). To configure your proxy settings manually specify +the address of the HTTP proxy in Proxy server and the +port the proxy listens on (normally 8080) in Port. Settings +will be saved in the ImageJ preferences file (IJPrefs.txt). + + +Compilersub:Compiler... + +Displays a dialog box with options for the CompilePluginssub:Compile-and-Run... +command. + + +minipage[c][1][t]0.37 +images/Compiler +minipage +minipage[c][1][t]0.63 +description +[Target] Specifies the Java version of the class files created +by Pluginssub:Compile-and-Run... Plugins compiled +with a Target of 1.6 will not run on earlier versions of Java. +A Target of 1.4 should be used to create plugins capable of +running on all versions ImageJ. Target cannot be set higher +than the version of Java ImageJ is currently running on.description + +minipage +description +[Generate Debugging Info (javac -g)] If checked, +information needed by Java Debugdebuggers will be included +in the class files. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/edit.html#compiler. +description + +[DICOM]DICOMsub:DICOM... + +minipage[c][1][t]0.27 +images/DICOMoptions +minipage +minipage[c][1][t]0.73 +This dialog sets options related to the handling of DICOMDICOM +images. Namely, if ImageJ should open DICOM images as 32-bit float, +if voxel depth should be calculated (based on the distance between +the first and last slice) and if coronal/transverse sections should +be mirrored when using the ImageStackssub:Orthogonal-Views +command. With IJ1.45, the DICOM reader applies the Rescale Slope +value when Open as 32-bit float is enabled and tag 0028,1053 +is not . + +sec:Image-Types +minipage + + +Miscsub:Misc... + +minipage[c][1][t]0.415 +images/Misc +minipage +minipage[c][1][t]0.585 +Displays a dialog box for configuring several (advanced) Settingssettings +that do not fit elsewhere in the ImageJ interface. +description +[Divide by zero value] Specifies the value used when +Processsub:Image-Calculator... detects a divide +by zero while dividing one 32-bit real image by another. The default +is infinity. In addition to numeric values, 'infinity' (positive +or negative infinity), 'max' (largest positive value) and 'NaN' +(Not-a-Number) can be entered as the Divide by zero value.description + +minipage +description +[Use pointer cursor] If checked, ImageJ will use an +arrow cursor instead of the default crosshair that is sometimes difficult +to see on grayscale images in areas of medium brightness. This option +can also be used to work around a bug on Windows where the text cursor +is sometimes used in place of the crosshair. Cursor@CursorPointer,PointerNote +that the default crosshair can be customized as explained in sec:GUIcustomization. +[Hide Process Stack? dialog] If +checked, ImageJ will suppress the dialog that asks 'Process all xx +slices?' (only the current slice will be processed). +[Require control/command key for shortcuts] If +checked, requires the Control key (Command key on Macs) to be pressed +when using keyboard shortcuts for menu commands. +[Move isolated plugins to Misc. menu] This option +can reduce the size of the Plugins menu, preventing it from running +off the bottom of the screen. When this option is enabled, plugins +that attempt to install themselves in a submenu with only one command +are instead installed in the PluginsMiscellaneous submenu. +An example of such a plugin is http://bigwww.epfl.ch/thevenaz/turboreg/TurboReg, +which normally creates a PluginsTurboReg submenu that +contains only one command. +[Run single instance listener] If +checked, ImageJ will use sockets to prevent multiple instances from +being launchedC-SocketListener. On Windows, this avoids the +problem where another copy of ImageJ starts each time an image is +dragged and dropped on the ImageJ icon. It also prevents multiple +instances when running ImageJ from the command line. Note that you +may get a security alert the first time ImageJ starts with this option +enabled. ImageJ does not require external socket access so it is okay +to deny it access in the security alert. This option is set by default +with new Windows installations. +[Debug mode] If checked, causes ImageJ to display debugging +messages in the sec:Log-Window. In addition, some commands +(e.g., ProcessBinarysub:Skeletonize +and sub:Watershed) produce detailed outputs when Debug +mode is active. Close the Log window to disable display of Debugdebugging +messages. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/edit.html#misc. +description +sec:GUIcustomization + + +[Reset]Resetsub:ResetOptionsNew command: EditOptionsReset + +minipage[c][1][t]0.445 +images/ResetOptions +minipage +minipage[c][1][t]0.555 +Causes the IJ preferences file (IJprefs.txt) to be deleted when +ImageJ quits, Resetresetting all parameters to their default +values when ImageJ is restarted. +minipage + +As mentioned in sec:Settings-and-Preferences, IJprefs.txt +holds all the settings and preferences of ImageJ and is stored in +/Library/Preferences/ on Mac OSX, in /.imagej/ on +Linux and Windows (with referring to the user's home directory). +Several macros and plugins also write parameters to this file. + +lis:setOption lis:setOption, PluginsUtilitiessub:Reset... + + + + +Imagesec:Image + + +Typesub:Type + +Use this submenu to determine the type of the active image or to convert +it to another type. An attempt to perform an unsupported conversion +causes a dialog box to be displayed that lists the possible conversions. +table[h] +Supported conversions in ImageJ (Imagesub:Type +submenu).Image types Note that ImageJ2 supports http://developer.imagej.net/imagej2-pixel-typesmany more types of image data. + + + +tabularl>m1.25cm>m1.25cm>m1.25cm>m1.25cm>m1.25cm>m1.25cm>m1.25cm + +1*From To & 8-bit & 16-bit & 32-bit & 8-bit color & RGB color & RGB stack & HSB stack8-bit & & I, S & I, S & & I, S & & 16-bit & I, S & & I, S & & I, S & & 32-bit & I, S & I, S & & & I, S & & 8-bit color & I, S & & & & I & & RGB color & I, S & & & I, S & & I, S & I, SRGB stack & & & & & I & & HSB stack & & & & & I & & 8lI:Single images only; S:Stackstabular +table + +description +[8-bit] Converts to 8-bit grayscale. ImageJ converts 16-bit +and 32-bit images to 8-bit by linearly scaling from min-max to +0-255, where min and max are the two values displayed +in the ImageAdjustsub:Brightness/Contrast...=00005BC=00005D. +Imagesub:Show-Info... displays these two values +as Display rangeDisplay range. Note that this scaling +is not done if Scale When Converting is not checked in EditOptionssub:Conversions... +RGB images are converted to grayscale using the formula +or +if Weighted RGB Conversions is checked in EditOptionssub:Conversions... +[16-bit] Converts to unsigned 16-bit grayscale. +[32-bit] Converts to signed 32-bit floating-point grayscale. +[8-bitColor] Converts to 8-bit indexed color using +Heckbert's median-cut http://en.wikipedia.org/wiki/Color_quantizationcolor quantization algorithm. +A dialog box allows the number of colors (2-256) to be specified. +The active image must be RGB color.Color!QuantizationColor!Quantization@Quantization Heckbert quantization,Heckbert quantizationAlgorithm!Heckbert quantization +[RGBColor] Converts to 32-bit RGB color. +[RGBStack] RGBConverts to a 3-slice (red, green, +blue) stack. The active image must be RGB color. +[HSBStack] HSBConverts to a 3-slice (hue, saturation +and brightness) stack. The active image must be RGB color. +description + +Adjustsub:Adjust + +This submenu contains commands that adjust brightness/contrast, threshold +levels and image size. + +infobox +infobox:AutoB=000026C-stacksApplying Auto Brightness/Contrast +to Entire Stacks + + +The Processsub:Enhance-Contrast command can +be used to adjust the Brightness/ContrastStacks!Brightness/Contrastbrightness +and contrast of each slice in a stack, according to either the optimal +for each individual slice (if Use Stack Histogram is unchecked) +or the overall stack (by ticking Use Stack Histogram). The +default behavior of the BC tool (ImageAdjustsub:Brightness/Contrast...=00005BC=00005D) +is to use the overall stack histogram. +infobox + + + +Brightness/Contrast [C]sub:Brightness/Contrast...=00005BC=00005D + +Use this tool to interactively alter the brightness and contrast of +the active image. With 8-bit images, brightness and contrast are +changed by updating the image's lookup table (LUT), so pixel values +are unchanged. With 16-bit and 32-bit images, the display is updated +by changing the mapping from pixel values to 8-bit display values, +so pixel pixel values are also unchanged. Brightness and contrast +of RGB images are changed by modifying the pixel values. + +minipage[c][1][t]0.235 +images/BC +minipage +minipage[c][1][t]0.765 +description +[Histogram] The line graph at the top of the window, which +is superimposed on the image's histogram, shows how pixel values are +mapped to 8-bit (0-255) display values. The two numbers under the +plot are the minimum and maximum displayed pixel values. These two +values define the display range, or 'window'. ImageJ displays images +by linearly mapping pixel values in the display range to display values +in the range 0-255. Pixels with a value less than the minimum are +displayed as black and those with a value greater than the maximum +are displayed as white. +[Minimum and Maximum sliders] Control the lower and +upper limits of the display range. Holding down Shift will simultaneously +adjust all channels of a composite image (e.g., FileOpen SamplesHeLa Cells (1.3M, 48-bit +RGB)).description + +minipageBrightness/ContrastLevels@Levels Brightness Contrast, +description +[Brightness slider] Increases or decreases image brightness +by moving the display range. Holding down Shift will simultaneously +adjust all channels of a composite image. +[Contrast slider] Increases or decreases contrast by varying +the width of the display range. The narrower the display range, the +higher the contrast. Holding down Shift will simultaneously adjust +all channels of a composite image. +[Auto] ImageJ will automatically optimize brightness and +contrast based on an analysis of the image's histogram. Create a selection, +and the entire image will be optimized based on an analysis of the +selection. The optimization is done by allowing a small percentage +of pixels in the image to become saturated (displayed as black or +white). Each additional click on Auto increases the number +of saturated pixels and thus the amount of optimization. + + A [basicstyle=]!run("Enhance Contrast", "saturated=0.35")! +macro call is generated if the command recorder (PluginMacrosub:Record...) +is running. +[Reset] Restores the original brightness and contrast settings. +The display range is set to the full pixel value range of the image. +A resetMinAndMax() macro call is generated if the command +recorder is running. Holding down Shift restores original settings +in all channels of a composite image. +[Set] Allows to enter the minimum and maximum display range +values in a dialog box. A setMinAndMax() macro call is generated +if the command recorder is running. + + +A 16-bit image consists of 65536possible gray levels. Most of +times, however, the relevant image information is contained only within +a narrow range of the grayscale. This is the case, e.g., in low light +microscopy, in which signal is restricted to the lower end of the +grayscale. The Set Display Range dialog allows you to choose +how to scale the range of gray levels of 16-bit images. + + +center +images/SetDisplayRange +center +description +[Automatic] Automatically selects the best range given the +intensity values of the image based on the percentage of the total +number of pixel values from the lowest to highest pixel value. +[8-bit (0-255)] Gray level range of 0-255. +[10-bit (0-1023)] Gray level range of 0-1023. +[12-bit (0-4095)] Gray level range of 0-4095. +[15-bit (0-32767)] Gray level range of 0-32767. +[16-bit (0-65535)] Gray level range of 0-65535. +description + +Check Propagate to +all open images to apply these values to the rest of the +images currently open. With multi-channel images, the option to propagate +the specified range to the remaining channels is also available. + +[Apply] Applies the current display range mapping function +to the pixel data. If there is a selection, only pixels within the +selection are modified. This option currently only works with 8-bit +images, 8-bit stacks and RGB stacks. This is the only BC +option that alters the pixel data of non-RGB images. +description +sub:Window/Level..., sub:Enhance-Contrast, sub:Color-Balance..., +infobox:AutoB=000026C-stacks infobox:AutoB=000026C-stacks, +infobox:Displaying-HDRI infobox:Displaying-HDRI, +infobox:DisplayRangeDICOM infobox:DisplayRangeDICOM + +infobox +infobox:DisplayRangeDICOMDisplay Range of DICOM Images + + +CTWith DICOMDICOM images, ImageJ sets +the initial display range based on the Window Center (0028,1050) +and Window Width (0028,1051) tags. Click Reset on +the WL (ImageAdjustsub:Window/Level...) +or BC (ImageAdjustsub:Brightness/Contrast...=00005BC=00005D) +window and the display range will be set to the minimum and maximum +pixel values. + + +As an example, the FileOpen SamplesCT (420K, 16-bit +DICOM) image has a Window Center of 50 and Window Width of 500, so the display +range is set to -200 to 300 (center-width/2 to center+width/2). Click +Reset and the display range is set to -719 to 1402. Press H +(Analyzesub:Histogram) and you will +see that the minimum pixel value in the image is -719 and the maximum +is 1402. + + +To display the DICOM tags, press I (Imagesub:Show-Info...). +Press R (Filesub:Revert=00005Br=00005D) +to revert to the initial display range. +infobox + + + +Window/Levelsub:Window/Level... + +minipage[c][1][t]0.475 +images/WindowLevel +minipage +minipage[c][1][t]0.525 +This command and sub:Brightness/Contrast...=00005BC=00005D +(BC) are redundant, but sub:Window/Level... +(WL) behaves in a manner closer to that implemented on medical +image terminals by interactively adjusting the Window - range +of minimum and maximum (Contrast) - and Level - position +of that range in the grayscale intensity space (Brightness). + + +If the BC window is opened, it will be closed and +the WL window will be opened at the same location. +minipageBrightness/ContrastLevels + + sub:Enhance-Contrast, sub:Color-Balance..., +infobox:AutoB=000026C-stacks infobox:AutoB=000026C-stacks, +infobox:Displaying-HDRI infobox:Displaying-HDRI,infobox:DisplayRangeDICOM +infobox:DisplayRangeDICOM + + +Color Balancesub:Color-Balance... + +This panel makes adjustments to the brightness and contrast of a single +color of a standard RGB image Color!Balance(8-bit per color +channel). + +minipage[c][1][t]0.405 +images/ColorBalance +minipage +minipage[c][1][t]0.595 +For multi-channels sub:Stacks-Intro and sub:Hyperstacks-Intro +(sub:Color-Composites) it adjusts each of the color channels +independently. Use the drop-down menu to specify which color/channel +will be adjusted (the histogram is drawn for the selected channel). + + +Maximum and Minimum sliders, Auto, Set +and Apply work as described for ImageAdjustsub:Brightness/Contrast...=00005BC=00005D. +Similarly to the sub:Window/Level... tool, if the BC +window is opened, it will be closed and the Color window will +be opened at the same location. + + +NB: When switching from one color to another, the changes made to +one color will be lost unless Apply is clicked before. Also, +note that for 48-bit color images that load as a stack, sub:Brightness/Contrast...=00005BC=00005D +works on single stack slices, i.e., colors, and the color settings +of the Color panel are ignored. +minipage + +sub:Brightness/Contrast...=00005BC=00005D, sub:ColorSubmenu +submenu + +infobox +infobox:Displaying-HDRIBrightness/Contrast of High Bit-Depth +Images + + +When displayed, the intensity of each pixel that is written +in the image file is converted into the grayness of that pixel +on the screen. How these intensities are interpreted is specified +by the image type. From the http://imagej.nih.gov/ij/docs/concepts.htmlImageJ website:Brightness/Contrast +quote +16-bit and 32-bit grayscale images are not directly displayable +on computer monitors, which typically can show only display 256shades +of gray. Therefore, the data are mapped to 8-bit by windowing. The +window defines the range of gray values that are displayed: values +below the window are made black, while values above the window are +white. The window is defined by minimum and maximum values that can +be modified using ImageAdjustsub:Brightness/Contrast...=00005BC=00005D. +quote +It may happen that the initial windowing performed by ImageJ on these +high bit-depth (or HDRHDRHigh Dynamic Range) images +is suboptimal. Please note that windowing does not affect image data +(cf. the http://imagej.nih.gov/ij/macros/tools/HDRexplorerTool.txtHDRexplorerTool). +infobox + + + +[Threshold [T]]Threshold [T]sub:Threshold...=00005BT=00005D + +Use this tool to automatically or interactively set lower and upper +Thresholdthreshold values, segmenting grayscale images into +features of interest and background. Use Analyzesub:Measure...=00005Bm=00005D) +(with Limitto Threshold in Analyzesub:Set-Measurements... +checked) to measure the aggregate of the selected features. Use Analyzesub:Analyze-Particles... +to measure features individually. Use the sub:Wand-Tool +to outline a single feature. +figure +images/ThresholdFlo:ImageAdjustImageAdjustsub:Threshold...=00005BT=00005D +(ImageJ1.45m). +figure +Huang@Huang Threshold,IsoData@IsoData Threshold,Li@Li Threshold,MaxEntropy@MaxEntropy Threshold,MinError@MinError Threshold,Moments@Moments Threshold,Otsu@Otsu Threshold,Renyi@Renyi Threshold,Shanbhag@Shanbhag Threshold,Yen@Yen Threshold, +description +[Upper slider] Adjusts the minimum threshold value. Hold +Shift while adjusting the minimum to move a fixed-width thresholding +window across the range of gray values. +[Lower slider] Adjusts the maximum threshold value. +[Method] Allows any of the 16 different automatic thresholding +methods to be selectedC-ThresMeth. These methods are described +on sub:Fiji-intro's http://fiji.sc/wiki/index.php/Auto_ThresholdAuto Threshold website. +The Default method is the modified IsoData algorithm used by +http://imagej.nih.gov/ij/docs/faqs.htmlautoImageJ 1.41 and earlier. +Note that these are global thresholding methods that typically cannot +deal with unevenly illuminated images (such as in http://imagejdocu.tudor.lu/doku.php?id=howto:working:how_to_correct_background_illumination_in_brightfield_microscopybrightfield microscopy). +In these cases, local algorithms are more appropriated, by allowing +the threshold to smoothly vary across the image.. These are implemented +by the http://fiji.sc/wiki/index.php/Auto_Local_ThresholdAuto Local Threshold +plugin, pre-installed in sub:Fiji-intro. +[Display] Selects one of three display modes:Black background + +description +[Red] Displays the thresholded values in red. description +lyxlist00000000000000 +[BW] Features are displayed in black +and background in white. This mode respects the Black background +flag set in ProcessBinarysub:BinaryOptions... +[Over/Under] Displays pixels below the +lower threshold value in blue, thresholded pixels in grayscale, and +pixels above the upper threshold value in green. These colors can +be changed from a macro by calling the ImageProcessor.setOverColor() +and setUnderColor() methods (http://imagej.nih.gov/ij/macros/examples/SetOverUnderThresholdColors.txtexample). +lyxlist +[Dark background] To be checked when features are lighter +than the background. The state of the checkbox is remembered across +restarts. +[Stack histogram] If checked, ImageJ will first compute +the histogram of the whole stack (or hyperstack) and then compute +the threshold based on that histogram. As such, all slices are binarized +using the single computed value. If unchecked, the threshold of each +slice is computed separately. +[Auto] Uses the currently selected thresholding method to +automatically set the threshold levels based on an analysis of the +histogram of the current image or selection. +[Apply] Sets thresholded pixels to black and all other pixels +to white. For 32-bit float images Apply will also run ProcessMathsub:NaN-Background. +[Reset] Disables thresholding and updates the histogram. +[Set] New threshold levels can be entered into this dialog +box. +description +infobox:InvertedLutMask infobox:InvertedLutMask, +sub:Color-Threshold..., sub:Wand-Tool, Analyzesub:Analyze-Particles... + + +Color Thresholdsub:Color-Threshold... + +Threshold!ColorColor!ThresholdThresholds 24-bit +RGBRGB images based on HSBHue Saturation and Brightness +(HSB), Red Green and Blue (RGB), CIE LabCIE Lab or YUVYUV +components. Ranges of the filters can be set manually or based on +the pixel value components of a user-defined ROI. This command, implemented +in version1.43l, is an experimental built-in version of the http://www.dentistry.bham.ac.uk/landinig/software/software.htmlThreshold Colour plugin +C-ColorThres and is not yet fully integrated into ImageJ. + +figure[H] +images/ThresholdColorSegmentation of DAPI stained nuclei using ImageAdjustsub:Color-Threshold... +figure + +description +[Pass] If checked, values within range are thresholded and +displayed (band-pass filter), otherwise, values outside the selected +range are thresholded (band-reject filter). +[Thresholding Method] Allows any of the 16different +automatic thresholding methods to be selected (see sub:Threshold...=00005BT=00005D). +[Threshold Color] Selects the threshold color: either +Red, Black, White or Black White (see +sub:Threshold...=00005BT=00005D). +[Color space] Selects the color space: HSB@HSBHSB, +RGB@RGBRGB, CIE@CIECIE +Lab or YUV@YUVYUV (see sub:Color-Spaces-and). +[Dark background] To be checked when features are lighter +than the background (see infobox:blackBackground infobox:blackBackground). +The state of the checkbox is remembered across restarts. +[Original] Restores the original image and updates the buffer +when switching to another image. +[Filtered] Shows the filtered image. Note that the final +thresholded image type is RGB, not 8-bit gray (see sec:Image-Types). +[Select] Creates a ROI selection based on the current settings. +The selection is made according to the settings defined in the ProcessBinarysub:BinaryOptions... +dialog. +[Sample] (Experimental) Sets the ranges of the filters based +on the pixel value components in a user-defined ROI. +[Stack] Processes the remaining slices of the stack (if +any) using the current settings. +[Macro] Creates a macro based on the current settings which +is sent to the Macro Recorder window (PluginsMacrossub:Record...), +if open. +[Help] Opens the built-in help dialog. +description +http://imagej.nih.gov/ij/plugins/color-inspector.html3D Color Inspector/Color Histogram, +sub:Threshold...=00005BT=00005D, sub:Wand-Tool, +Analyzesub:Analyze-Particles... + + +[Size]Sizesub:Size... + +minipage[c][1][t]0.487 +images/Resize +minipage +minipage[c][1][t]0.513 +Scales the active image or selection to a specified Width and +Height in pixels. + + +Check Constrain aspect ratio and ImageJ will adjust either +the Height or the Width to maintain the original Aspect ratioaspect +ratio. When applicable, other dimensions can also be resized: Depth (images) +in stacks, Depth (slices) and Time (frames) +in hyperstacks. + + + + +Check the Average when downsizing checkbox for better results +when Downsizingscaling down imagesC-Resizer-Scaler. +Two Resampling@Resampling Interpolation,resampling +methods are possible: Bilinear interpolation@Bilinear interpolation Interpolation,Bilinear +and Bicubic interpolation@Bicubic interpolation Interpolation,Bicubic +Interpolationinterpolation. The implementation of the bicubic +method (Catmull-Rom@Catmull-Rom Interpolation,Catmull-Rom +interpolation) is derived from Burger and Burge, 2008Burger:2008p14082. +minipage + +sub:Canvas-Size..., Imagesub:Scale...=00005BE=00005D, +ImageTransformsub:Bin... + + +[Canvas Size]Canvas Sizesub:Canvas-Size... + +minipage[c][1][t]0.42 +images/ResizeCanvas +minipage +minipage[c][1][t]0.58 +Changes the Canvascanvas size without scaling the actual +image. Width and Height may be either expanded or contracted. +If the canvas size is increased, the border is filled with the current +background color (see sub:Color-Picker...=00005BK=00005D), +or, if Zero Fill is checked, the border is filled with pixels +that have a value of zero. The position of the old image within the +new canvas may also be specified. + +sub:Size..., Imagesub:Scale...=00005BE=00005D, +ImageTransformsub:Bin..., infobox:Color +infobox:Color +minipage + + +Line Widthsub:Line-WidthSlider + +minipage[c][1][t]0.456 +images/LineWidth2 +minipage +minipage[c][1][t]0.544 +This widget is used to adjust the width of line selections (in pixels). +It is opened more easily by double clicking on the sec:Line-Selection-Tools +icon. Checking Spline Fit fits a cubic spline curve to the +points that define the line. +minipage + +EditOptionssub:Line-Width..., EditSelectionsub:Fit-Spline + + +[Show Info [i]]Show Info [i]sub:Show-Info... + +minipage[c][1][t]0.45 +images/Info +minipage +minipage[c][1][t]0.55 +Opens a text window containing information about the active image +(including the pixel or voxel size, since IJ1.44k). For DICOM and +FITS images, also displays file Metadataheader information. +Use the popup menu (right-click in the Info window) to save the information +to a text file or copy it to the system clipboard. + +Imagesub:Image>Properties... +minipage + + +Properties [P]sub:Image>Properties... + +minipage[c][1][t]0.306 +images/ImageProperties +minipage +minipage[c][1][t]0.694 +Use this command to display and set various properties of the current +image or stack. + + +The number of Channels (c), Slices (z) and Frames +(t) in the image can be changed as long as the product of c, +z, and t is equal to the number of images in the stack. + + +Unit of Length is a string describing the measuring unitCalibration!Spatial +of Pixel sizePixel Width, Pixel Height and +Voxel depthVoxel Depth. These three dimensions are +automatically converted if Unit of Length is changed from one +of ImageJ's known unit ('nm', 'm' [or 'um' or 'micron'], +'mm', 'cm', 'meter', 'km' or 'inch') to another. +and symbols can be typed using AltM and AltShiftA, +respectively. + + + + +With t-series stacks, the Frame intervalFrame Interval +in seconds (reciprocal of the frame rate) can be viewed and set. +If the unit is 'sec', setting the Frame Interval will also +set the frame rate used by sub:Animation-Options.... +minipage + +Origin is the reference point (always in pixels) of +the image coordinate system (see also misc:InvertYcoordinates +in Analyzesub:Set-Measurements...). + +As explained in infobox:GlobalCal infobox:GlobalCal, +check Global to make the current settings global, i.e., applied +to all images opened during the current session. + +Analyzesub:Set-Scale..., Imagesub:Show-Info... + + +Colorsub:ColorSubmenu + +This submenu contains commands that deal with color images. + + +Split Channelssub:Split-Channels + +Splits an RGB image (or stack) into three 8-bit grayscale images +containing the red, green and blue components of the originalChannels. +The window names have an appended (red), (green) and +(blue). With composite images and/or hyperstacks (e.g., +FileOpen SamplesOrgan of Corti (2.8M, 4D stack)) +this command splits the stack into separate channels. + +sub:Merge-Channels... + + +[Merge Channels]Merge Channelssub:Merge-Channels...ImageColorMerge Channels extended to 7 channels + +Merges 2-7 images into an RGB image or multi-channel composite image. +Select the channel order/color using the C1-C7 dropdown menus. +Select *None* to skip a channel. + +minipage[c][1][t]0.33 +images/MergeChannels +minipage +minipage[c][1][t]0.67 +description +[Create composite] If checked, a multi-channel composite +image (see sub:Color-Composites) will be created. +If unchecked, an RGB image is created instead. When creating composite +images, original LUTs and display ranges are preserved unless Ignore +source LUTs is checked. Source LUTs are always ignored when creating +RGB images. +[Keep source Images] If checked, source images will +not be disposed. +[Ignore source LUTs] If checked, LUTs of source images +are ignored. In this case, merged channels will adopt the lookup table +mentioned besides the channel choice, i.e., red, green, +blue, gray, cyan, magenta, yellow. +As mentioned, this option is assumed when merging into RGB.description + +minipage + +sub:Channels...=00005BZ=00005D, sub:Lookup-Tables +and infobox:Replacing-Red-w-Magenta infobox:Replacing-Red-w-Magenta + + +Channels Tool [Z]sub:ChannelsTool-Color + +Alias for ImageHyperstackssub:Channels...=00005BZ=00005D. + + +Stack to RGBsub:Stack to RGB + +Converts a two or three slice stack into an RGB image, assuming that +the slices are in R, G, B order. The stack must be 8-bit or 16-bit +grayscale. Also converts composite images (e.g., FileOpen SamplesHeLa Cells (1.3M, 48-bit RGB)) +into RGB. + + +Make Compositesub:Make-Composite + +minipage[c][1][t]0.353 +images/MakeComposite +minipage +minipage[c][1][t]0.647 +Converts in place an RGB image, a 2-7 image stack or a 2-7 channel +hyperstack into a composite color image. Use the sub:Channels...=00005BZ=00005D +tool (Shift Z) to enable and disable the channels of a composite +image. Use sub:Brightness/Contrast...=00005BC=00005D (Shift +C) to adjust the brightness and contrast of the current channel. +minipage + + +Show LUTsub:Show LUT + +minipage[c][1][t]0.438 +images/ShowLut +minipage +minipage[c][1][t]0.562 +Displays a plot of the active image's lookup table (LUT) . The lookup +table, or color table, describes the color that is displayed for each +of the 256 possible pixel values. For 16 and 32-bit images, the range +of displayed pixel values is mapped to 0-255. A bar under the plot +displays the color representation of the pixel values. Note that RGB +color images do not use a lookup table. Use the List radio +button to export the LUT as a CSVCSVComma-Separated Values +file. + +sub:Edit-LUT +minipage + + +Edit LUTsub:Edit-LUT + +minipage[c][1][t]0.407 +images/EditLut +minipage +minipage[c][1][t]0.57 +Opens the ImageJ LUT (Lookup Table) Editor. A lookup table in ImageJ +has up to 256 entries. The entry index, and the three values (red, +green and blue) associated with it, are displayed in the ImageJ status +bar as you move the cursor over the LUT Editor window. Click on an +entry to edit the red, green and blue values for that entry using +a Color Selector window (cf. sub:Color-Picker...=00005BK=00005D). + +sub:Show LUT +minipage + + +Color Picker [K]sub:Color-Picker...=00005BK=00005D + +AnnotationsColor!ForegroundColor!BackgroundThe +Color PickerC-CP enables the user to select foreground and +background colors, which affects Editsub:Fill-=00005Bf=00005D, +sub:Draw-=00005Bd=00005D, sub:Clear and other +drawing commands. It displays current foreground and background colors +in the selection boxes at the bottom of the window. It has two modes: +Foreground and Background. To change modes, click on +the desired selection box. Clicking on the Foreground/Background +Switcher button sets the current foreground to the background +and vice versa. The Black/White Reset button sets the +foreground to black and the background to white. +figure[h] +images/CP[Color Picker window]fig:CPtoolColor Picker and Color Choosers (IJ1.46c). +The CP window can be activated using Shift K (the keyboard shortcut +for ImageColor sub:Color-Picker...=00005BK=00005D) +or by double clicking on the sec:Color-Picker on the ImageJ +sub:Toolbar. Color Choosers are evoked by double clicking +on a color of the CP window and can be used to retrieve infobox:HEX. +The 'eye dropper' is drawn in the current foreground color while +the frame around it is drawn in background color. Foreground color +is also reflected in drawing tools such as the sub:ArrowTool2, +sub:Brush, sub:FloodFiller and sub:Pencil +tools. +figure + + +The color palette is based on HSB (Hue, Saturation and Brightness) +color model (see sub:Color-Spaces-and). Hue increases +as you go down the palette while saturation and brightness values +are split horizontally. The left half of the palette varies only in +brightness while the right half varies only in saturation. At the +center of the color ramp are enlarged red, green, blue, cyan, magenta, +and yellow colors for quick selection. To the left of the color palette +is a grayscale ramp that goes from pure black to pure white. + +ColorChoosers display hex color valuesDouble clicking +on a color brings up the ColorChooser, a widget with three sliders +used to specify the RGB values of the foreground or background color. +The title of the ColorChooser widget (Foreground Color or Background +Color) indicates the current selection mode. To get precise colors, +manually change the values in the text boxes. The Hexadecimal (Hex colors)hex +value of the final color is also displayed, offering a convenient +way to retrieve custom colors to, e,g, personalize sub:Overlay-Intro +(see infobox:HEX infobox:HEX). + +As mentioned earlier, the sec:Color-Picker tool can be +used to 'pick-up' foreground/background colors from an image canvas. +Foreground color can also be changed using the Color dropdown +menu in the Options dialog of drawing tools such as sub:ArrowTool2, +sub:Brush, sub:OverlayBrush and sub:Pencil +tools. + +infobox:Color infobox:Color, sub:Draw-=00005Bd=00005D, +sub:Fill-=00005Bf=00005D, sub:Clear, sub:Clear-Outside, +sec:Image-Types, lis:toolsShrtct3 + +infobox +infobox:ColorEmbedding Color Annotations in Grayscale Images + + +Annotations!Grayscale imagesColor marks are only +available with color images or grayscale images that have been converted +to RGB (Imagesub:Type submenu). For +non-RGB images, background/foreground color will be drawn in +equivalent gray levels, e.g.: For a 8-bit image, if the foreground +color is red (RGB: 255, 0, 0) intensity of drawn selections will be +. + + +Colored sub:Overlay-Intro (see Imagesub:Overlay, +sub:OverlayBrush tool), on the other hand, can be created +on all image types becoming the easiest way to annotate grayscale +images. +infobox + + + +Stackssub:Stacks + +This submenu contains commands related to sub:Stacks-Intro. +Operations specifically related to sub:Hyperstacks-Intro +are listed in the Imagesub:Hyperstacks submenu. + + +[Add Slice]Add Slicesub:Add-Slice + +minipage[c][1][t]0.275 +images/AddSlice +minipage +minipage[c][1][t]0.725 +Inserts a blank slice after the currently displayed slice. Holding +Alt inserts a blank slice before the current slice. With sub:Hyperstacks-Intro, +a dialog prompt allows to insert either a channel, z-slice or t-frame. + +sub:Delete-Slice +minipage + + +[Delete Slice]Delete Slicesub:Delete-Slice + +minipage[c][1][t]0.337 +images/DeleteSlice +minipage +minipage[c][1][t]0.663 +Deletes the currently displayed slice. With sub:Hyperstacks-Intro, +it can delete the current channel, z-slice or t-frame. + +sub:Add-Slice +minipage + + +Next Slice [>]sub:Next-Slice-=00005B>=00005D + +Displays the slice that follows the currently displayed slice. Holding +Alt > will skip ten slices forward. + +Arrow-Keys + + +Previous Slice [<]sub:Previous-Slice-=00005B>=00005D + +Displays the slice that precedes the currently displayed slice. Holding +Alt < will skip ten slices backward. + +Arrow-Keys + + +Set Slicesub:Set-Slice... + +minipage[c][1][t]0.33 +images/SetSlice +minipage +minipage[c][1][t]0.67 +Displays a specified slice. The user must enter a slice number greater +than or equal to one and less than or equal to the number of slices +in the stack. +minipage + + +Images To Stacksub:Images-To-Stack + +Creates a new stack from images currently displayed in separate windows. +description +[Method] If images differ in size, a drop-down menu allows +to choose a conversion method: +description +minipage[c][1][t]0.52 +images/ImageToStacks +minipage +minipage[c][1][t]0.48 +description +[Copy (center) and Copy (top-left)] Stack +will have the width of the widest open image and the height of the +highest open image. Smaller images will then be copied (either to +the center or to the upper left corner) of the slice. Borders are +filled with pixels that have a value of zero. +[Scale (smallest) and Scale (largest)] Stack +will have the dimensions of the smallest/largest open image. +Other images are scaled to the new slice dimensions. Bicubic interpolation +is used if Bicubic interpolation is checked (cf. Imagesub:Size... +and Imagesub:Scale...=00005BE=00005D).description + +minipage +description +[Name] Specifies the title of the stack to be created. +[Title Contains] Enter a string into this field and ImageJ +will only convert to stack images whose name contains that string. +[Bicubic Interpolation] If checked, bicubic interpolation +(cf. Adjustsub:Size...) will be used if any +of the Scale methods was previously chosen. +[Use Title as Labels] If checked, image titles (without +extension) will be used as stack labels. As described in StacksToolssub:Remove-Slice-Labels, +these labels (up to 60 characters) correspond to the image subtitle, +the line of information above the image. +[Keep Source Images] If checked, original images are +kept. +description + +Stack To Imagessub:Stack-To-Images + +Converts the slices in the current stack to separate image windows. + +Stackssub:Images-To-Stack + + +[Make Montage]Make Montagesub:Make-Montage + +figure +images/MakeMontage +figure +Stacks!MontageMontage@Montage Stacks (Montage),Panel figures@Panel figures Stacks (Montage),Produces +a single grid-image containing the individual images that compose +sub:Stacks-Intro and 4D sub:Hyperstacks-Intro. +This can be useful for visual comparisons of a series of images stored +in a stack and to create 'panel figures' for publication and presentations. +A dialog box allows you to specify the magnification level at which +the images are copied, and to select the layout of the resulting grid. +description +[Label Slices] If checked, montage panels are labelled +with slice labels. Slice labels (up to 60 characters) correspond to +the image subtitle, the line of information above the image. These +labels are part of the stack metadata, typically created by FileImportsub:Image-Sequence... or +Stackssub:Images-To-Stack. If no slice metadata +exists (the http://imagej.nih.gov/ij/developer/macro/functions.htmlsetMetadatasetMetadata("Label", string) +macro function can be used to customize slice labels) images are labelled +with slice numbers. Note that the Stackssub:Label... +command can be used to draw labels in stack slices. Labels are typeset +in sans-serif typeface. +[Use Foreground Color] If checked, borders and labels +are drawn in the foreground color and blank areas of the panel are +filled with the background color. +description +StacksToolspar:Montage-to-Stack..., +StacksToolssub:Remove-Slice-Labels, +http://imagej.nih.gov/ij/plugins/rc-montage/index.htmlRC Montage +plugin, http://imagejdocu.tudor.lu/doku.php?id=howto:working:work_with_magic_montageMagic Montage +- a macro toolset to reorder and manipulate images in the montage +(a video tutorial can be found http://imagejdocu.tudor.lu/doku.php?id=video:utilities:creating_montages_with_magic_montagehere) + + +[Reslice [/]]Reslice [/]sub:Reslice...=00005B/=00005D + +minipage[c][1][t]0.41 +images/Reslice +minipage +minipage[c][1][t]0.59 +Reconstructs one or more orthogonal slices through the image volume +represented by the current stack or hyperstackC-Reslice-Zproj. + + +The estimated size of the output stack and the amount of available +memory are displayed at the bottom of the dialog. Increase Output +spacing to reduce the size of the output stack. + + +A dialog allows you to specify the spacing of the reconstructed slices. +minipage +description +[Output spacing] Determines the number of orthogonal slices +that will be reconstructed. Increasing Output spacing reduces +the size of the output stack. +[Start at] Determines the image edge (top, left, +bottom or right) from which reconstruction starts. Start +at is replaced by Slice count if there is a line selection. +With lines selections, a stack is created by shifting (by Output +spacing) the line down and to the left to generate additional slices +for the output stack. In this case, the size of the output stack in +determined by Slice count. +[Flip vertically] If checked, each slice in the output +stack will be flipped vertically. +[Rotate 90 degrees] If checked, each slice in the output +stack will be rotated 90. +[Avoid interpolation] If checked, no interpolation will +be done. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/image.html#reslice. +description +http://fiji.sc/wiki/index.php/Dynamic_ResliceDynamic Reslice +and http://imagej.nih.gov/ij/plugins/radial-reslice/index.htmlRadial Reslice +plugins + + +Orthogonal Views [H]sub:Orthogonal-Views + +minipage[c][1][t]0.475 +images/OrthogonalViews +minipage +minipage[c][1][t]0.525 +Provides an Orthogonal viewsorthogonal view display of the +current stack or hyperstackC-OrthoViews. E.g., if a stack +displays Sagittal@Sagittal Orthogonal views,sagittal +sections, Coronal@Coronal Orthogonal views,coronal +(YZ projection image) and transverse (XZ Projectionprojection +image) will be displayed through the data-set. + + +The two extra Planar views@Planar views Orthogonal views,planar +views are displayed in 'sticky' panels next to original image and +can be toggled using Shift H, the command shortcut. + + +The intersection point of the three views follows the location of +the mouse click and can be controlled by clicking and dragging in +either the XY, XZ or YZ view. XY and XZ coordinates are displayed +in the title of the projection panels. The mouse wheel changes the +screen plane in all three views. + + +Voxel dimensions can be adjusted in Imagesub:Image>Properties.... +minipage + +sub:3D-Project..., and (hreeD viewer@3D Viewer3D Viewerhttp://fiji.sc/wiki/index.php/3D_Viewer3D Viewer +Schmid:2010p18702, http://imagej.nih.gov/ij/plugins/volume-viewer.htmlVolume Viewer, +http://imagej.nih.gov/ij/plugins/stack-slicer/index.htmlStack Slicer +http://www.med.harvard.edu/JPNM/ij/plugins/Display3TP.htmlDisplay3TP +plugins, EditOptionssub:DICOM... + + +[Z Project]Z Projectsub:Z-Project... + +Projects an image stack along the axis perpendicular to image plane +(the so-called z axis)C-Reslice-Zproj. With Z Projection@Z Projection Projection,Stacks!Projection@Projection Projection,hyperstacks, +the projection is performed on the active time frame, or for all time +points if All Time Frames is checked. Five different projection +types are supported. The preferred projection method is stored in +the preferences file. + +minipage[c][1][t]0.485 +images/Zproject +minipage +minipage[c][1][t]0.515 +description +[Average Intensity] projection outputs an image wherein +each pixel stores average intensity over all images in stack at corresponding +pixel location. +[Maximum Intensity] projection (MIPMIPMaximum Intensity Projection) +MIP@MIP Projection,creates an output image each of +whose pixels contains the maximum value over all images in the stack +at the particular pixel location.description + +minipage +description +[Sum Slices] projection creates a real image that is the +sum of the slices in the stack. +[Standard Deviation] projection creates a real image containing +the standard deviation of the slices. +[Median] projection outputs an image wherein each pixel +stores median intensity over all images in stack at corresponding +pixel location. +description +par:Grouped-Z-Project, sub:3D-Project..., sub:Plot-Z-axis-Profile... + + +[3D Project]3D Projectsub:3D-Project... + +minipage[c][1][t]0.43 +images/3D-Project +minipage +minipage[c][1][t]0.57 +This command creates a sequence of projections of a rotating volume +Three D Projection @3D Projection3D Projection(stack +or hyperstack) onto a plane using nearest-point (surface), +brightest-point, or mean-value projection or a weighted +combination of nearest point projection with either of the other two +methods (partial opacity)C-3Dproject. The user may choose +to rotate the volume about any of the three orthogonal axes (x, y, +or z), make portions of the volume transparent (using thresholding), +or add a greater degree of visual realism by employing depth cues. + + +Each frame in the animation sequence is the result of projecting from +a different viewing angle. To visualize this, imagine a field of parallel +rays passing through a volume containing one or more solid objects +and striking a screen oriented normal to the directions of the rays. +minipage + +Each ray projects a value onto the screen, or Projectionprojection +plane, based on the values of points along its path. Three methods +are available for calculating the projections onto this plane: nearest-point, +brightest-point, and mean-value. The choice of projection +method and the settings of various visualization parameters determine +how both surface and interior structures will appear. +description +[Projection Method] Select Nearest Point projection +to produce an image of the surfaces visible from the current viewing +angle. At each point in the projection plane, a ray passes normal +to the plane through the volume. The value of the nearest non transparent +point which the ray encounters is stored in the projection image. +Brightest Point projection examines points along the rays, +projecting the brightest point encountered along each ray. This will +display the brightest objects, such as bone in a CTCTComputed TomographyCT +(computed tomographic) study. Mean Value projection, a modification +of brightest-point projection, sums the values of all transparent +points along each ray and projects their mean value. It produces images +with softer edges and lower contrast, but can be useful when attempting +to visualize objects contained within a structure of greater brightness +(e.g. a skull). +[Slice Spacing] The interval, in pixels, between the slices +that make up the volume. ImageJ projects the volume onto the viewing +plane at each Rotation Angle Increment, beginning with the +volume rotated by Initial Angle and ending once the volume +has been rotated by Total Rotation. +[Lower/Upper Transparency Bound] Determine the +transparency of structures in the volume. Projection calculations +disregard points having values less than the lower threshold or greater +than the upper threshold. Setting these thresholds permits making +background points (those not belonging to any structure) invisible. +By setting appropriate thresholds, you can strip away layers having +reasonably uniform and unique intensity values and highlight (or make +invisible) inner structures. Note that you can also use ImageAdjustsub:Threshold...=00005BT=00005D +to set the transparency bounds. +[Opacity] Can be used to reveal hidden spatial relationships, +especially on overlapping objects of different colors and dimensions. +The (surface) Opacity parameter permits the display of weighted +combinations of nearest-point projection with either of the other +two methods, often giving the observer the ability to view inner structures +through translucent outer surfaces. To enable this feature, set Opacity +to a value greater than zero and select either Mean Value or +Brightest Point projection. +[Surface/Interior Depth-Cueing] Depth cues can +contribute to the three-dimensional quality of projection images by +giving perspective to projected structures. The depth-cueing parameters +determine whether projected points originating near the viewer appear +brighter, while points further away are dimmed linearly with distance. +The trade-off for this increased realism is that data points shown +in a depth-cued image no longer possess accurate densitometric values. +Two kinds of depth-cueing are available: Surface Depth-Cueing +and Interior Depth-Cueing. Surface Depth-Cueing works +only on nearest-point projections and the nearest-point component +of other projections with opacity turned on. Interior Depth-Cueing +works only on brightest-point projections. For both kinds, depth-cueing +is turned off when set to zero (i.e. 100 of intensity in back +to 100 of intensity in front) and is on when set at n 100 (i.e. (n) +of intensity in back to 100 intensity in front). Having independent +depth-cueing for surface (nearest-point) and interior (brightest-point) +allows for more visualization possibilities. +[Interpolate] Check Interpolate to generate a temporary +z-scaled stack that is used to generate the projections. Z-scaling +eliminates the gaps seen in projections of volumes with slice spacing +greater than 1.0pixels. This option is equivalent to using the +http://www.imagescience.org/meijering/software/transformj/scale.htmlScale +plugin from the http://www.imagescience.org/meijering/software/transformj/TransformJ +package to scale the stack in the z-dimension by the slice spacing +(in pixels). This checkbox is ignored if the slice spacing is less +than or equal to 1.0pixels. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/image.html#project. +description +sub:Orthogonal-Views, sub:Z-Project..., par:Grouped-Z-Project +and http://fiji.sc/wiki/index.php/3D_Viewer3D ViewerSchmid:2010p18702, +http://imagej.nih.gov/ij/plugins/volume-viewer.htmlVolume Viewer +plugins + + +Plot Z-axis Profilesub:Plot-Z-axis-Profile...Plot profileZ ProfileStacks!Profile + +minipage[c][1][t]0.48 +images/Zprofile +minipage +minipage[c][1][t]0.52 +Plots the ROI selection mean gray value versus slice number. Requires +a point or area selection. + + +Coordinates of the upper left corner of the selection (or the bounding +rectangle for non-rectangular selections) are displayed in the graph +title. + +sub:Profile-Plot-Options..., sub:Plot-Profile-=00005Bk=00005D +minipage + + +[Label]Labelsub:Label... + +minipage[c][1][t]0.35 +images/Label +minipage +minipage[c][1][t]0.65 +Adds a sequence of numbers (e.g., timestamps) and/or a label to a +stack or hyperstack. Numbers and label are drawn in the current foreground +color (cf. ImageColorssub:Color-Picker...=00005BK=00005D). + + + +The initial X,Y location, and Font size of the label +are based on the existing rectangular selection, if any. Slices outside +the Range are not affected. +description +[Format] Specifies the structure of the label. 0: +Unpadded sequence; 0000: Pads each number with leading zero(s); +00:00: Converts the label into a minutes:seconds +timestamp; 00:00:00 Converts the label into a hours:minutes:seconds +timestamp; Text: Stamps only the contents of the Text +field. Label: Displays slice labels. description + +minipageStacks!LabelingTime stamper +description +[Starting value and Interval] Specify the first +value and the numeric steps to be applied. Note that with timestamps, +metric time values must be used, e.g., an Interval of 3600 +will create 1hour increments. +[Text] The string to be drawn after each number when the +Format chosen is either 0 or Text (label without +numeric sequence). +[Use overlay] If checked, labels will be created as non-destructive +image sub:Overlay-Intro. Note that previously added overlays +will be removed. Also, note that sub:Virtual-Stacks and +sub:Hyperstacks-Intro can only have overlay labels. +[Use text tool font] If checked, labels will be created +using the typeface and style specified in the sub:Fonts... +widget. If unchecked, labels are typeset using ImageJ's default font: +sans-serif typeface. +[Help] Opens http://imagej.nih.gov/ij/docs/menus/image.htmllabelhttp://imagej.nih.gov/ij/docs/menus/image.htmllabel. +description +sub:Make-Montage, StacksToolspar:Insert... + + +Toolssub:Stack>ToolsStacks!Tools + + +Combinesub:Combine... + +minipage[c][1][t]0.335 +images/Combine +minipage +minipage[c][1][t]0.665 +CombineCombines two stacks [WidthHeightDepth] +(WHD and WHD) +to create a new WWmax(H,H)max(D,D) +stack. E.g., a 25625640 and a 25625630 +stack would be combined to create one 51225640 stack. + + +If Combine vertically is enabled, creates a new max(WW)(HH)max(D,D) +stack. +minipage + +Unused areas in the combined stack are filled with background color +(cf. sub:Color-Picker...=00005BK=00005D). + +sub:Concatenate... + + +[Concatenate]Concatenatesub:Concatenate...Improved ImageStacksToolsConcatenate + +minipage[c][1][t]0.328 +images/Concatenate +minipage +minipage[c][1][t]0.672 +ConcatenateConcatenates multiple images or stacks. Images +with mismatching type (see sec:Image-Types) and +dimensions are omittedC-Concatenator. Stacks with the same +number of slices can be concatenated as a 4D sub:Hyperstacks-Intro, +if Open as 4D image is checked. In this case, chosen stacks +will be appended as time-points. + +sub:Combine... +minipage + + +Reducesub:Reduce... + +minipage[c][1][t]0.302 +images/ReduceSize +minipage +minipage[c][1][t]0.698 +Reduces the size of stacks and hyperstacks by the specified Reduction +Factor. E.g., For a 30slices stack and a Reduction Factor +of 2, the reduced stack will be be composed of 15slices with every +second slice being removed. Virtual stacks/hyperstacks are supported + + + +With Hyperstacks, the default reduction is performed in the T-Dimension, +but a choice is available to Reduce in Z-Dimension instead. +minipageReduceStacks!Reduce + +Hyperstackssub:Reduce-Dimensionality... + + +Reversesub:Reverse + +Alias for the ImageTransformsub:Flip-Z +command. + + +[Insert]Insertpar:Insert... + +minipage[c][1][t]0.365 +images/StackInserter +minipage +minipage[c][1][t]0.635 +Inserts a Source image into a Destination image at the +specified X and Y Location (pixel coordinates). +Source and Destination can be single images or stacks +but must be of the same type (see sec:Image-Types). +The Destination image will be permanently modified once Source +has been inserted. Note that when Source is a single image, +EditSelectionsub:Image-to-Selection... +can be used (together with ImageOverlaysub:Add-Image...) +to create image selections (ImageROIs), a more convenient way of blending +two open images. +minipageStacks!Labeling + +Imagesub:Type, ImageStackssub:Label... + + +Montage to Stackpar:Montage-to-Stack...Stacks!Montage + +minipage[c][1][t]0.32 +images/StackMaker +minipage +minipage[c][1][t]0.68 +Converts a montage image to an image stack based on the specified +number of rows and columns, taking into account a Border width. +This is the opposite of what the ImageStackssub:Make-Montage +command does. + +http://imagej.nih.gov/ij/plugins/demontager.htmlDemontager +plugin +minipage + + +[Make Substack]Make Substackpar:Make-Substack + +minipage[c][1][t]0.456 +images/MakeSubstack +minipage +minipage[c][1][t]0.544 +Extracts selected images from the active stack copying them to a new +stack in the order of listing or rangingC-SubstackMaker. +Stacks!SubstacksStacks!ReduceDuplicate + + + + +Extracted slices will be removed from the source stack if Deleted +slices from original stack is checked. Currently, it does not work +with hyperstacks and takes one of three types of input: +minipage +enumerate +A range of images. E.g.: 2-14 [extract slices 2 +through 14] +A range of images with increment, which can be used to De-interleaveInterleavede-interleave +slices. E.g.: 2-14-2 [extract slices 2 and +14 and every second slice in between] +A list of images. E.g.: 2,4,7,9,14 +enumerate +Imagesub:Duplicate...=00005BD=00005D + + +[Grouped Z Project]Grouped Z Projectpar:Grouped-Z-Project + +Grouped Z ProjectionProjectionZ Projection@Z Projection Projection,Stacks!Projection@Projection Projection,Stacks!ReduceCreates +a substack of slices with each slice being +the result of a Z Projection performed over the range of . + +minipage[c][1][t]0.5 +images/GroupedZproject +minipage +minipage[c][1][t]0.5 + must divide evenly into the stack size. This +limitation can be overcome by the ImageTransformsub:Bin..., +that can also create grouped Z-projections. + + +The first ten divisors of are suggested at the bottom +of the dialog. +minipage + +ImageStackssub:Z-Project..., ImageAdjustsub:Size..., +ImageAdjustsub:Scale...=00005BE=00005D + + +[Remove Slice Labels]Remove Slice Labelssub:Remove-Slice-Labels + +Removes slice labels from stacks. The first line of a slice label +(up to 60 characters) is displayed in parentheses in the image subtitle, +the line of information above the image. The macro functions http://imagej.nih.gov/ij/developer/macro/functions.htmlsetMetadatasetMetadata("Label", string) +and http://imagej.nih.gov/ij/developer/macro/functions.htmlgetMetadatagetMetadata("Label") +can be use to set and retrieve the current slice label. + +Stackssub:Label... + + +Start Animation []sub:Start-Animation + +Animates the active stack by repeatedly displaying its slices (frames) +in sequence. It is run more easily by clicking on the play icon preceding +stack sliders (see sub:Stacks-Intro). To stop the +animation, click on the slider pause icon, click on the image or use +sub:Stop-Animation, evoked by the same shortcut. As such, +stacks animation can be toggled using . The frame +rate is displayed in the status bar. Open the sub:Animation-Options... +dialog box to specify the animation speed (pressing Alt +or right-clicking on the on the slider play/pause icon opens the Animation Options dialog). +Note that more than one stack can be animated at a time. + + +Stop Animation []sub:Stop-Animation + +Terminates animation of the active stack (see sub:Start-Animation). + + +Animation Options [Alt/]sub:Animation-Options... + +minipage[c][1][t]0.315 +images/AnimationOptions +minipage +minipage[c][1][t]0.685 +Use this dialog to set the animation speed in frames per secondfpsFrames Per Second, +the starting and ending frame, or to enable 'oscillating' animations. +Selecting Start Animation animates the stack as soon as the +dialog is dismissed. + + + + +Note that setting the Frame Interval in Imagesub:Image>Properties... +sets the animation speed as long as the unit used is 'sec'. +minipageAnimation + +This dialog can also be accessed by right-clicking on the play/pause +icon that precedes the slice slider in sub:Stacks-Intro +and frame slider in sub:Hyperstacks-Intro (see fig:Stacks-and-Hyperstacks). + +FileSave Assub:Gif..., sub:SaveAs>Avi... + + +Hyperstackssub:Hyperstacks + +This submenu hosts commands specifically related Stacks!HyperstacksHyperstackssub:Hyperstacks-Intro, +images that have four (4D) or five (5D) dimensions. General operations +related to sub:Stacks-Intro are listed in the Imagesub:Stacks +submenu. + + +New Hyperstacksub:New-Hyperstack... + +minipage[c][1][t]0.39 +images/NewHyperstack +minipage +minipage[c][1][t]0.61 +Creates a new hyperstack. sub:Hyperstacks-Intro have Width, +Height, Channels (c dimension), Slices (z dimension) +and time Frames (t dimension). + + + + +Image Type (see Imagesub:Type +and sec:Image-Types) and Display Mode (see +sub:Channels...=00005BZ=00005D) can be specified. + + +Checking Label Images will draw the channel number, slice number +and frame number on each image in the hyperstack. + +FileNewsub:Hyperstack... +(an alias of this command) and FileNewsub:Image...=00005Bn=00005D +minipage + + +[Stack to Hyperstack]Stack to Hyperstacksub:Stack-to-Hyperstack... + +minipage[c][1][t]0.44 +images/StackToHyperstack +minipage +minipage[c][1][t]0.56 +Converts a stack into a hyperstack. RGB stacks are converted into +3 channel hyperstacks. + + +Order is the order of the channels (c), slices (z) +and frames (t) within the stack. ImageJ hyperstacks are always +in czt order. Stacks not in czt order will be shuffled +to be in czt order. The channel Display Mode can be Composite, +Color or Grayscale (cf. sub:Channels...=00005BZ=00005D). + +sub:Hyperstack-to-Stack +minipage + + +[Hyperstack to Stack]Hyperstack to Stacksub:Hyperstack-to-Stack + +Converts a hyperstack into a stack (in czt order). + +sub:Stack-to-Hyperstack... + + +Reduce Dimensionalitysub:Reduce-Dimensionality... + +This commandC-ReduceDimens ReduceStacks!Reducereduces +the dimensionality of an hyperstack by creating a new hyperstack with, +for example, all the channels and time points at a given z position +or all the z slices for the current channel and time point. + +minipage[c][1][t]0.26 +images/ReduceDimensionality +minipage +minipage[c][1][t]0.74 +Uncheck Channels(n) to delete all but the current channel, +Slices(n) to delete all but the current z slice and Frames(n) +to delete all but the current time point. Check Keep Source +and the original stack will not be deleted. + + +The expected dimensions and size of the reduced stack are displayed +in the dialog. + +sub:Hyperstack-to-Stack +minipage + + +Channels Tool [Z]sub:Channels...=00005BZ=00005D + +ChannelsOpens the fig:Channels-tool, or brings +it to the front if it is already open. Shift Z is the keyboard shortcut +for this command. This tool allows to select the Display mode +of composite images. In addition, several commands hosted in the Imagesub:ColorSubmenu +submenu can easily be accessed through the More +drop-down menu. The same drop-down menu also provides a convenient +list of primary colors (additive: red, green and blue, subtractive: +cyan, magenta, yellow) that can be used to pseudocolor sub:Color-Composites. + +figure[h] +images/ChannelsTool[Channels widget]fig:Channels-toolChannel manipulations in sub:Color-Composites + using the ImageColorsub:Channels...=00005BZ=00005D +tool. +figure + + + +[Crop [X]]Crop [X]sub:Crop-=00005BX=00005D + +CropCrops the image or stack based on the current rectangular +selection. + + +[Duplicate [D]]Duplicate [D]sub:Duplicate...=00005BD=00005D + +minipage[c][1][t]0.32 +images/Duplicate +minipage +minipage[c][1][t]0.68 +Creates a new window containing a copy of the active image or rectangular +selection. For stacks and hyperstacks it is possible to specify the +range of Channels (c), Slices (z) and Frames (t) +to be duplicated. + + +With single images, hold Alt to skip the dialog box. + +sub:Rename... +minipageDuplicate + + +Renamesub:Rename... + +minipage[c][1][t]0.41 +images/Rename +minipage +minipage[c][1][t]0.59 +Renames the active image. + +sub:Duplicate...=00005BD=00005D +minipage + + +[Scale [E]]Scale [E]sub:Scale...=00005BE=00005D + +minipage[c][1][t]0.36 +images/Scale +minipage +minipage[c][1][t]0.64 +Resizes the image or current area selection by scale factors entered +into a dialog box. As with Imagesub:Size..., +two resampling methods are possible: Bilinear and Bicubic +interpolation. + + +For the best looking results, particularly with graphics and text, +use integer scale factors (2, 3, 5, etc.) and check Average +when downsizing with scale factors less than 1.0C-Resizer-Scaler. +Also, when downsizing, smoothing the source image prior to scaling +may produce better looking results. + + +Scaled image/selection are copied to a new image named Title +if Create new window is checked. If scaling a selection that +will not be copied to a new image check Fill with Background +Color to fill with the background color instead of zero. + + +Entire stacks (or hyperstacks in the Z Dimension) will be scaled if +Process entire stack is checked. +minipageScaleDownsizing + +ImageAdjustsub:Size..., ImageTransformsub:Bin..., +ImageStacksToolspar:Grouped-Z-Project + + +Transformsub:Transform + +This submenu contains commands that perform geometrical image transformation +on the active image or stack.Transform + + +Flip Horizontallysub:Flip-Horizontally + +Replaces the image or selection with a x-mirror image of the original. + + +Flip Verticallysub:Flip-Vertically + +Turns the image or selection upside down (y-mirror). + + +Flip Zsub:Flip-Z + +Reverses the order of the slices in a stack (z-mirror). + + +[Rotate 90 Degrees Right]Rotate 90 Degrees Rightsub:Rotate-90-Degrees-R + +Rotates the entire image or stack clockwise 90. + + +[Rotate 90 Degrees Left]Rotate 90 Degrees Leftsub:Rotate-90-Degrees-L + +Rotates the entire image or stack counter-clockwise 90. + + +Rotate + +minipage[c][1][t]0.595 +images/Rotate +minipage +minipage[c][1][t]0.405 +Use this dialog to rotate the active image or selection clockwise +the specified number of degrees. + + +Set Grid Lines to a value greater than zero to superimpose +a grid on the image in Preview mode. Two resampling methods +are possible: Bilinear and Bicubic interpolation (cf. Imagesub:Size...). +minipageRotate + +With 8-bit and RGB images, check Fill with Background Color +to fill with the background color instead of zero (cf. sub:Color-Picker...=00005BK=00005D). +Check Enlarge to Fit Result and the image will be enlarged +as needed to avoid clipping. + + +Translate + +minipage[c][1][t]0.337 +images/Translate +minipage +minipage[c][1][t]0.663 +Translates (moves) the image in the x and y directions by a specified +number of pixels. With stacks, you can translate either the current +image or all the images in the stack. Two resampling methods are possible: +Bilinear and Bicubic interpolation (cf. Imagesub:Size...). + + + +Check Preview to see how the translation will affect the image. +The background at the edges of the image will be set to 0. +minipageTranslate + +http://www.dentistry.bham.ac.uk/landinig/software/software.htmlAlignSlice and AlignRGBplanes +plugins + + +[Bin]Binsub:Bin...New command: ImageTransformBin + +minipage[c][1][t]0.337 +images/Bin +minipage +minipage[c][1][t]0.663 +Reduces the size of an image by binning groups of pixels of user-specified +size (X,Y,Z shrink factor)C-Binner. The resulting +pixel can be calculated as Average, Median, Maximum, +or Minimum. Undo support is restricted to 2D images (non stacks). + + +Z binning produces equivalent results to ImageStacksToolspar:Grouped-Z-Project +However, there are two main differences between the two commands: +While Bin replaces the original image, par:Grouped-Z-Project +creates a new substack; and while Z shrink factor takes any +value, Group size must divide evenly into the stack size. +minipage + +ImageAdjustsub:Size..., ImageAdjustsub:Scale...=00005BE=00005D, +ImageStacksToolspar:Grouped-Z-Project + + +[Image to Results]Image to Resultssub:ImageToResultsNew commands: ImageTransformImage to Results and Results to Image + +minipage[c][1][t]0.416 +images/ImageToResults +minipage +minipage[c][1][t]0.584 +Prints the active area selection to the sec:Results-Table, +clearing previous results. The entire image is processed when no area +ROI exists. XY coordinates are detailed in column and row headers. +Calibrated and floating-point images are listed with the precision +specified by Decimal places in Analyzesub:Set-Measurements... + + + +For RGB images, each pixel is converted to grayscale using the formula + or the formula + +if Weighted RGB to Grayscale Conversion is checked in EditOptionssub:Conversions... +minipage + +fig:TextImages, sub:PixelInspector, sub:ResultsToImage, +FileSave Assub:SaveAs>Text-Image..., +Importsub:Import>Text-Image, http://imagej.nih.gov/ij/macros/js/Stack_to_Results.jsStacktoResults.js, +a script that displays the contents of a stack using one image per +column + + +[Results to Image]Results to Imagesub:ResultsToImage + +The reverse of sub:ImageToResults, converting the tabular +data in the sec:Results-Table into a 32-bit image named +Results Table. Column and row headers are ignored. + +fig:TextImages, sub:PixelInspector, FileSave Assub:SaveAs>Text-Image..., +Importsub:Import>Text-Image + + +Zoomsub:Zoom + +This submenu contains commands that control how the current image +is displayed. The and or and keys +are the preferred way to use the sub:ZoomIn and sub:ZoomOut +commands.Zoom When a selection exists, zooming with the Arrow-Keys +requires holding down either Shift or Ctrl. + + +[In [+]]In [+]sub:ZoomIn + +Zooms in to next higher magnification level and, if possible, enlarges +the window. As explained in sec:Magnifying-Glass, there +are 21possible levels (shown in the title bar): 3.1, 4.2, 6.3, +8.3, 12.5, 16.7, 25, 33.3, 50, 75, 100, 150, 200, 300, 400, 600, 800, +1200, 1600, 2400 and 3200. + +infobox +infobox:ZoomedCanvasWorking with Zoomed Canvases + + + +minipage[c][1][t]0.231 +images/ZoomIndicator +minipage +minipage[c][1][t]0.769 +Images are magnified using and , or and +if no selection exists. Magnification occurs around the cursor, or +to the center of the image when the cursor lays outside the image +canvas. The Zoom indicator in the upper left corner of magnified +images shows what portion of the image is currently displayed. At +high magnification levels the pixel grid becomes visible by default +unless Interpolate zoomed images is checked in EditOptionssub:Appearance... +To scroll a magnified image, hold down the space bar (sec:Scrolling-Tool +shortcut) while dragging the cursor. +minipage + + + + +By default, sub:Overlay-Intro and the active selection +are displayed with a 1-pixel wide contour regardless of the image +magnification (0 Width). To thicken ROI edges at higher zoom +levels, set Stroke width to a non-zero value in EditSelectionsub:Properties..., +ImageOverlaysub:Overlay-Options... +or fig:The-ROI-Manager's misc:RM-Properties +infobox + + + +Out [-]sub:ZoomOut + +Zooms out to next lower magnification level and, if needed, shrinks +the window. + + +Original Scale [4]sub:Original-Scale-=00005B4=00005D + +Displays the image at the magnification used when the image was first +opened. As a shortcut, double click on the sec:Magnifying-Glass +tool. + + +View 100 [5]sub:View-100=000025-=00005B5=00005D + +Displays the image using 100 magnification (1image pixel = 1screen +pixel). Enable Open Images at 100 in the EditOptionssub:Appearance... +dialog to have images automatically opened at 100 magnification. + + +To Selectionsub:ZoomToSelection + +Zooms in based on the current selection. Note that in the absence +of a selection, this command zooms the image to a fit to screen +level (see sec:Magnifying-Glass). Zoom!Fit to Screen + + +[Set]Setsub:Set-Zoom... + +minipage[c][1][t]0.26 +images/SetZoom +minipage +minipage[c][1][t]0.74 +Zooms the active image to an exact value (e.g. 37.4) overcoming +the predefined zoom steps described in ImageZoomsub:ZoomIn. +The zoomed canvas will be centered at X,Y center (pixel coordinates) +C-SetZoom. +minipage + + +Overlaysub:Overlay + +OverlayNon-destructive annotations@Non-destructive annotations Overlay,Annotations!Non-destructive image overlayAs +mentioned previously, this submenu contains commands for creating +and working with non-destructive image sub:Overlay-Intro. +An overlay consists of one or more selections: arrows, lines, points, +shapes and text (see ImageJ sub:Toolbar). Overlays +can also be composed of image selections (Image selection@Image selection ImageROIImageROIimageROIs) +that behave partially as regular sec:Selections-Intro (see +sub:Add-Image...). + +Press B (sub:Add-Selection...=00005Bb=00005D) to add the +current selection to the overlay. Press Shift F (sub:Flatten-=00005BF=00005D) +to create an RGB image with the overlay embedded in it. The overlay +is preserved when an image is saved in TIFF format (cf. infobox:Formats +infobox:Formats).Blend +figure[h] +images/OverlayExamples[examples]fig:image-overlaysNon-destructive image sub:Overlay-Intro. +Heat-mapsOutputs from http://imagej.nih.gov/ij/macros/examples/Grid_Overlay.txtGridOverlay, +http://imagej.nih.gov/ij/macros/examples/MakeOverlay.txtMakeOverlay +and http://imagejdocu.tudor.lu/doku.php?id=macro:roi_color_coderROI Color Coder +that exemplify the usage of most Imagesub:Overlay +submenu commands. The sub:OverlayBrush tool can also be +used to create freehand annotations. +figure + + + +[Add Selection [b]]Add Selection [b]sub:Add-Selection...=00005Bb=00005D + +minipage[c][1][t]0.373 +images/AddToOverlay +minipage +minipage[c][1][t]0.627 +Selections are immediately added to the current overlay when pressing +B. Pressing Alt B will display a dialog box in which Stroke +color and width and Fill color can be set. + + +Except for text selections, and as explained in EditSelectionsub:Properties..., +Stroke (contour) color and Width are ignored if a Fill +color is specified. Colors are specified using the name of one of +the default selection colors (black, blue, cyan, +green, magenta, orange, red, white +and yellow) or using hex notation (see infobox:HEX +infobox:HEX). + + +Previously added sub:Overlay-Intro are removed if New +overlay is checked. Also, if no selection exists and the command +is run, a warning message is displayed in which is possible to remove +the existing overlay, by running sub:Remove-Overlay. + + +Note that measured selections (Analyzesub:Measure...=00005Bm=00005D) +can be added automatically to the image overlay by selecting the Add +to overlay checkbox in Analyzesub:Set-Measurements... +minipage + +sub:Overlay-Options..., sub:Labels..., Selectionsub:Properties..." +infobox:HEX infobox:HEX, sub:ROI-Manager... + + +[Add Image]Add Imagesub:Add-Image... + +BlendBlends two open images by adding an image to the Overlayoverlay +of frontmost image. The image to be blended can be of any type (see +sec:Image-Types) but cannot be larger than the host image. +A Annotation!Layers@Layers ImageROI, Overlay,Layers@Layers ImageROI, Overlays,blending +alpha value can be specified in the Opacity (0-100) field. +The initial X,Y location is based on the existing rectangular selection, +if any. + +minipage[c][1][t]0.35 +images/AddImage +minipage +minipage[c][1][t]0.65 +By default the created overlay image cannot be moved around the canvas, +i.e" is not a image selection (ImageROI), but are stored in the TIFF +header and can be saved and restored when saving images in TIFF format. +On the other hand, image selections can be created using EditSelectionsub:Image-to-Selection... +or by running ImageOverlaysub:To-ROI-Manager +after adding the image to the overlay. + +sub:Paste-Control...(Blend transfer mode), ImageStacksToolspar:Insert... +minipage + +infobox +infobox:HEXHexadecimal Color Values + + +Hexadecimal (Hex colors)http://en.wikipedia.org/wiki/HexadecimalHexadecimal (hex) +notation is frequently used in computing to summarize binary code +in a human-friendly manner. Here are some decimal/hexadecimal equivalents: + + + +centering + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/plain/06-shortcuts.txt b/plain/06-shortcuts.txt new file mode 100644 index 0000000..5e2187b --- /dev/null +++ b/plain/06-shortcuts.txt @@ -0,0 +1,278 @@ + +Keyboard Shortcutssec:Keyboard-Shortcuts + +The following table summarizes the keyboard Shortcutsshortcuts +built into ImageJ. You can create additional shortcuts, or override +built-in ones, by http://imagej.nih.gov/ij/developer/macro/macros.htmlshortcutscreating simple macros +and adding them to the StartupMacros.txt. You can also assign a function +key to a menu command using PluginsShortcutssub:Create-Shortcuts.... + +Several of these shortcuts accept key modifiers as described in sec:Key-Modifiers. +Also note that, except when using the sec:Text-Tool, you +do not need to hold down the control key to use a keyboard shortcut, +unless Require control key for shortcuts in EditOptionssub:Misc... +is checked. + +sub:Using-Shortcuts, sec:Finding-Commands, http://imagej.nih.gov/ij/macros/KeyboardShortcuts.txtKeyboardShortcuts.txt +macro (demonstrating how to assign shortcuts to custom macros), sub:Tools-shortcuts + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/plain/07-credits.txt b/plain/07-credits.txt new file mode 100644 index 0000000..3cd86d9 --- /dev/null +++ b/plain/07-credits.txt @@ -0,0 +1,249 @@ +sec:credits +thebibliographyReferences +C-WindowsInstallerThe ImageJ installer for Windows is created +using the http://www.jrsoftware.org/isinfo.phpInno Setup +installer generator. ImageJ.exe the Windows that launches ImageJ +(ij.jar) was contributed by George Silva. + +C-ZIPcompressedTIFFsSupport for ZIP-compressed TIFFs was +contributed by Jason Newton in IJ1.45g. + +C-FxFinderThe macro editor's Function Finder (MacrosFind Functions...) +was written by Jrme Mutterer. + +C-EllipseToolThe sub:Elliptical-Selection-Tool +was contributed by Norbert Vischer. + +C-ROIbrushThe sub:Brush-Selection-Tool is based +on the http://imagej.nih.gov/ij/plugins/roi-brush.htmlROI Brush Tool +plugin from Tom Larkworthy and Johannes Schindelin. + +C-ArrowToolJean-Yves Tinevez and Johannes Schindelin (authors +of the http://fiji.sc/wiki/index.php/ArrowFiji Arrow Tool) +contributed code to the sec:Arrow-Tool. + +C-WandToolMichael Schmid, added 4-connected and 8-connected +tracing with tolerance to the sub:Wand-Tool. + +C-ToolsetsMacro Toolsets distributed with ImageJ have been +contributed by Gilles Carpentier, Jrme Mutterer and Tiago Ferreira. + +C-PixelInspectorThe sub:PixelInspector is a +plugin tool conversion of Michael Schmid's http://imagejdocu.tudor.lu/doku.php?id=plugin:utilities:pixel_inspector:startPixel Inspector +plugin. + +C-ImportResultsIn IJ1.43l and earlier, the FileImportsub:Import>Results +command was based on Jrme Mutterer's http://imagej.nih.gov/ij/macros/Import_Results_Table.txtImportResultsTable +macro. + +C-StackFromListMarcel van Herk added URLs support to the +FileImportsub:Stack-From-List... +command in IJ1.45f. + +C-AviPluginsMichael Schmid contributed improvements to +the http://imagej.nih.gov/ij/source/ij/plugin/AVI_Reader.javaAVI reader +and http://imagej.nih.gov/ij/source/ij/plugin/filter/AVI_Writer.javaAVI writer +plugins. + +C-FITSwriterKaren Collins contributed improvements to the +FITSWriter (FileSave Assub:FITS... +command). + +C-FitCircleThe EditSelectionsub:Fit-Circle +command, based on a MATLAB script by http://www.math.uab.edu/ chernov/cl/MATLABcircle.htmlNikolai Chernov, +was contributed by Michael Doube and Ved Sharma. + +C-CreateSelectionThe EditSelectionsub:Create-Selection +command is based on the ThresholdToSelection plugin written by +Johannes Schindelin. + +C-SocketListenerIJ1.46f adopted Johannes Schindelin's +RMI-based http://fiji.sc/javadoc/fiji/OtherInstance.htmlOtherInstance +class from Fiji, which works on multi-user machines and is more secure. + +C-CPThe Color Picker (ImageColorsub:Color-Picker...=00005BK=00005D) +was written by Gali Baler, a 2003-2004 intern from http://www.montgomeryschoolsmd.org/schools/bcchs/Bethesda-Chevy Chase High School. + +C-ThresMethThe 16different thresholding methods available +in the ImageAdjustsub:Threshold...=00005BT=00005D +tool were implemented by Gabriel Landini. + +C-Resizer-ScalerMichael Schmid contributed improvements +to the downsizing kernel used by ImageAdjustsub:Size... +and Imagesub:Scale...=00005BE=00005D +as well as undo support for Imagesub:Scale...=00005BE=00005D. + +C-ColorThresThe ImageAdjustsub:Color-Threshold... +command implements Gabriel Landini's http://www.dentistry.bham.ac.uk/landinig/software/software.htmlThreshold Colour plugin. + +C-Reslice-ZprojThe http://imagej.nih.gov/ij/source/ij/plugin/Slicer.javaReslice +and the http://imagej.nih.gov/ij/source/ij/plugin/ZProjector.javaZProject +plugin (ImageStackssub:Reslice...=00005B/=00005D +and sub:Z-Project... commands) were contributed by Patrick +Kelly and Harvey Karten of the University of California, San Diego. + +C-OrthoViewsThe ImageStackssub:Orthogonal-Views +command is based on Dimiter Prodanov's http://imagej.nih.gov/ij/plugins/stack-slicer/index.htmlStackSlicer +plugin and Albert Cardona's Updater class. Michael Doube added support +for XZ and YZ view control as well as mouse wheel control. + +C-3Dproject-1The ImageStackssub:3D-Project... +was written by Michael Castle and Janice Keller of the University +of Michigan Mental Health Research Institute (MHRI). Bill Mohler added +suport for hyperstacks and 16/32-bit images in IJ1.44m. + +C-ConcatenatorThe ImageStacksToolssub:Concatenate... +command implemented in IJ1.46e is based on the http://imagej.nih.gov/ij/plugins/concatenate.htmlConcatenate +plugin by Jonathan Jackson. + +C-SubstackMakerThe ImageStacksToolspar:Make-Substack +command is based on the http://imagej.nih.gov/ij/plugins/substack-maker.htmlSubstack Maker +plugin by Anthony Padua, Daniel Barboriak and Ved Sharma. + +C-ReduceDimensThe ImageHyperstackssub:Reduce-Dimensionality... +command is based Jrme Mutterer's http://imagej.nih.gov/ij/macros/Reduce_HyperStack.txtReduce HyperStack +macro. + +C-BinnerThe ImageTransformsub:Bin... +command is based on Nico Stuurman's http://valelab.ucsf.edu/ nico/IJplugins/Binner.htmlBinner +plugin. + +C-SetZoomThe ImageZoomsub:Set-Zoom... +command is based on Albert Cardona's http://albert.rierol.net/software.htmlZoom Exact +plugin. + +C-Find-MaximaThe Processsub:Find-Maxima +command is based on a plugin contributed by Michael Schmid. + +C-EnhContrastThe equalization code implemented in Processsub:Enhance-Contrast +was contributed by Richard Kirk. + +C-RemoveNaNsThe ProcessNoisesub:Remove-NaNs...was +contributed by Michael Schmid. + +C-MathMacroThe ProcessMathsub:Macro... +command is modeled after Ulf Dittmer's http://www.ulfdittmer.com/imagej/index.htmlExpressionExpression +plugin. + +C-FFTfilterThe ProcessFFTsub:Bandpass-Filter... +is a built in version of Joachim Walter's http://imagej.nih.gov/ij/plugins/fft-filter.htmlFFT Filter +plugin. + +C-Fill-HolesThe ProcessBinarysub:Fill-Holes +algorithm was contributed by Gabriel Landini. + +C-Skeletonize3DThe http://fiji.sc/wiki/index.php/Skeletonize3DSkeletonize3D +plugin was written by Ignacio Arganda-Carreras, based on an ITKInsight Segmentation and Registrationhttp://itk.org/itkindex.htmlITK +implementation by http://hdl.handle.net/1926/1292Hanno Homann. +It implements a 3D thinning algorithm from Lee et al. http://dx.doi.org/10.1006/cgip.1994.1042Building skeleton models via 3-D medial surface axis thinning algorithms. CVGIP, +56(6):462-478, 1994. + +C-MultiThreadFiltersMulti-threading support for all Processsub:Filters +commands was contributed by Stephan Saalfeld and Michael Schmid in +ImageJ1.45c. + +C-GaussianBlurThe faster and more accurate version of +ProcessFilterssub:Gaussian-Blur... +implemented in ImageJ1.38r was contributed by Michael Schmid. + +C-NonBlockingDialogThe NonBlockingGenericDialog.class +used by the ProcessBatchsub:batch>Macro... +command was added by Johannes Schindelin. + +C-SubtractBackgroundThe rolling ball code of Processsub:Subtract-Background... +is based on the NIH Image Pascal version by Michael Castle and Janice +Keller. The sliding paraboloid algorithm was written by Michael Schmid. + +C-DistributionThe Analyzesub:Distribution... +command was written by Gabriel Landini. + +C-HistogramThe scaled color bar implemented in Analyzesub:Histogram +was contributed by Bob Dougherty. + +C-CurveFitterThe much improved http://imagej.nih.gov/ij/developer/api/ij/measure/CurveFitter.htmlCurveFitter +(AnalyzeToolssub:Curve-Fitting...) +implemented in IJ1.46f was contributed by Michael Schmid. The Rodboard +and Gaussian functions were originally contributed by David Rodbard +(NIH) and Stefan Worz (DKFZ), respectively. + +C-RM-XORThe ROI Manager(XOR) command (AnalyzeToolssub:ROI-Manager...) +was added by Johannes Schindelin. + +C-RM-MultiMeasureThe ROI Manager(Multi Measure) +command (AnalyzeToolssub:ROI-Manager...) +is based on Bob Dougherty's MultiMeasure plugin. + +C-RM-MultiPlotThe ROI Manager(Multi Plot) command +(AnalyzeToolssub:ROI-Manager...) +was contributed by Philippe Gendre. + +C-SyncWIndowsThe AnalyzeToolssub:SynchronizeWindows +command (an improved version of the http://imagej.nih.gov/ij/plugins/ucsd.htmlSyncWindows plugin +by Patrick Kelly) was contributed by Joachim Walter. + +C-ControlPanelThe Control Panel (PluginsUtilitiessub:Control-Panel...) +was written by Cezar M. Tigare. + +C-ComandFinderThe Command Finder (PluginsUtilitiessub:Command-Finder) +was written by Mark Longair. + +C-PluginToolThe http://imagej.nih.gov/ij/source/ij/plugin/tool/PlugInTool.javaPlugInTool +class was inspired by Johannes Schindelin's http://fiji.sc/javadoc/fiji/tool/AbstractTool.htmlAbstractTool +class in Fiji. + +C-SeveralOther additions, improvements and reproducible + bug reports have been contributed by Adrian Daerr, Airen Peraza, +Ajay Gopal, Albert Cardona, Alberto Duina, Alden Dima, Andreas Maier, +Andrew French, Andrii Savchenko, Arttu Miettinen, Aryeh Weiss, Balazs +Nyiri, Barry DeZonia, Bill Mohler, Bob Hamilton, Bob Loushin, Bruno +Vellutini, Burri Olivier, Carlos Becker, Carne Draug, Charles Anderson, +Cheryl McCreary, Christian Moll, Christophe Leterrier, Christopher +Harrison, Damon Poburko, Daniel Hornung, Daniel Kalthoff, Daniel Senff, +David Gauntt, David McDonald, Denny Hugg, Dimiter Prodanov, Divakar +Ramachandran, Dorai Iyer, Duncan Mak, Eik Schumann, Emmanuel Levy, +Erik Meijering, Fabian Svara, Francis Burton, Frank Sprenger, Franklin +Shaffer, Frederic Hessman, Gabriel Landini, Gilles Carpentier, Gregory +Reneff, Hiroki Hakoshima, Ian Lim, Ingo Bartholomaeus, Jakob Preus, +Jamie Robinson, Jan Eglinger, Jan Funke, Jarek Sacha, Jay Unruh, Jean-Pierre +Clamme, Jerome Mutterer, Jesper Pedersen, Jim Passmore, Joachim Wesner, +Johannes Hermen, Johannes Schindelin, Johannes Weissmann, John Oreopoulos, +John Pearl, Jonathan Silver, Jose Wojnacki, Juan Grande, Julian Cooper, +Kai Uwe Barthel, Karen Collins, Kees Straatman, Kevin Moll, Kris Sheets, +Mark Krebs, Mark Longair, Martin Dressler, Mat Al-Tamimi, Matthew +Smith, Michael Cammer, Michael Doube, Michael Ellis, Michael Schmid, +Michel Julier, Nagananda Gurudev, Nico Stuurman, Norbert Vischer, +Olaf Freyer, Oliver Bannach, Olivier Bardot, Paul Jurczak, Peter Haub, +Rainer Engel, Raymond Coory, Reinhard Mayr, Richard Cole, Richie Mort, +Robert Dougherty, Shannon Stewman, Simon Roussel, Stefan Starke, Stephan +Saalfeld, Steven Green, Thomas Boudier, Thorsten Wagner, Tiago Ferreira, +Tomas Karlsson, Tseng Qingzong, Ulf Dittmer, Uwe Walschus, Valerio +Mussi, Ved Sharma, Vytas Bindokas, Wilhelm Burger, Winfried Wurm, +Xiao Chen, Zeljka Maglica. + +thebibliography + + +infobox +infobox:focusFocus on Bioimage Informatics + + +In July 2012 Nature Methods issued a http://www.nature.com/nmeth/focus/bioimageinformatics/index.htmlfocus +dedicated to the role of bioimage informatics in microscopy, the tools +that are available for scientific image processing, and the challenges +and opportunities in the field. The special issue features a large +collection of articles discussing ImageJ, sub:Fiji-intro +and sub:Related-Software, including: +itemize +Cardona A, Tomancak P: "Current challenges in open-source +bioimage informatics"Cardona:2012p21002 +Carpenter AE et al.: "A call for bioimaging software usability" +Carpenter:2012p21003 +Eliceiri KW. "Biological imaging software tools"Eliceiri:2012p21007 +Schindelin J et al. "Fiji: an open-source platform for +biological-image analysis"Schindelin:2012p21012 +Schneider CA et al.: "NIH Image to ImageJ: 25 years of +image analysis"Schneider:2012p20999 +itemize +A full announcement can be found on the http://fiji.sc/wiki/index.php/2012-06-29_-_Fiji_papers_at_Nature_MethodsFiji news channel. +infobox + diff --git a/plain/08-biblio.txt b/plain/08-biblio.txt new file mode 100644 index 0000000..789ef72 --- /dev/null +++ b/plain/08-biblio.txt @@ -0,0 +1,4396 @@ + + + + + + +The following references are a small sample (particularly biased +towards the life sciences) of the bibliography directly related +to ImageJ, the standard in scientific image analysis. These +publications include: 1) technical articles and books describing +routines implemented in ImageJ, 2) research articles that have +made extensive use of ImageJ as a scientific tool or 3) reviews +that discuss ImageJ pertinently. A similar list is maintained on +the [sub:Fiji-intro] [http://fiji.sc/wiki/index.php/Publications||website] +. + + +To cite ImageJ one of the citations is possible (see [http://imagej.nih.gov/ij/docs/faqs.html#cite||FAQs] +): + +1. Rasband WS. ImageJ, U.S. National Institutes of Health, + Bethesda, Maryland, USA, [http://imagej.nih.gov/ij/||imagej.nih.gov/ij/] + , 1997--2012. + +2. Abràmoff MD, Magalhães PJ and Ram SJ. “Image Processing with + ImageJ”, Biophotonics International, 11(7):36--42, 2004 ([http://webeye.ophth.uiowa.edu/dept/biograph/abramoff/imagej.pdf||PDF] + ) [rec-number 5]. + +3. Schneider CA, Rasband WS and Eliceiri KW. “NIH Image to + ImageJ: 25 years of image analysis”, Nature Methods, pp. 671, + 2012 [3] + +To cite [sub:Fiji-intro]: + +• Schindelin J et al. “Fiji: an open-source platform for + biological-image analysis”, Nature Methods, pp. 676--82, 2012 [2] + +To cite this document: + +• Ferreira T and Rasband WS. “ImageJ User Guide --- IJ 1.46”, [http://imagej.nih.gov/ij/docs/guide/||imagej.nih.gov/ij/docs/guide/] + , 2010--2012 + + + +Gassmann:2009p20997 +Quantifying Western blots: pitfalls of densitometry (article) +Author +Max Gassmann and Beat Grenacher and Bianca Rohde and Johannes Vogel +Journal +Electrophoresis +Year +2009 +Volume +30 +Number +11 +Pages +1845--55 +Month +Jun +Keywords +Algorithms, Blotting: Western, Densitometry, Erythropoietin, Linear Models, Animals, Image Processing: Computer-Assisted, Humans, Radioimmunoassay +Abstract +Although Western blots are frequently quantified, densitometry is not documented and appears to be based merely on traditions and guesswork. Confirming previous experience, none of 100 randomly selected and systematically scanned most recent papers provided sufficient information on how Western blot results were translated into statistical values. The importance of such information, however, becomes evident from our correlations of plasma erythropoietin values of various mammals determined using RIA and Western blot densitometry. Different common densitometry procedures applied to the identical Western blot revealed p-values of these correlations ranging from 0.000013 to 0.76 reflecting the necessity of a scientifically sound basis for densitometry of Western blots. At present, the current lack of any definitions in densitometry opens the door to uncontrollable acquisition of any desired p-value. Here we provide data that define what should be considered, what avoided and what documented when quantifying Western blots. +Affiliation +Institute of Veterinary Physiology, Vetsuisse Faculty University of Zürich and Zürich Center for Integrative Human Physiology, University of Zürich, Switzerland. +Date-Added +2012-07-04 15:53:49 -0400 +Date-Modified +2012-07-04 15:53:49 -0400 +Doi +10.1002/elps.200800720 +Language +eng +Pmid +19517440 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1002/elps.200800720 + +Myers:2012p21009 +Why bioimage informatics matters (article) +Author +Gene Myers +Journal +Nat Meth +Year +2012 +Volume +9 +Number +7 +Pages +659--660 +Month +Jun +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-02 16:01:24 -0400 +Doi +10.1038/nmeth.2024 +Language +en +Rating +0 +Url +http://www.nature.com/nmeth/journal/v9/n7/full/nmeth.2024.html +Local Files + +Remote URLs +http://www.nature.com/nmeth/journal/v9/n7/full/nmeth.2024.html +http://dx.doi.org/10.1038/nmeth.2024 + +Ronneberger:2012p21008 +ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains (article) +Author +Olaf Ronneberger and Kun Liu and Meta Rath and Dominik Ruess and Thomas Mueller and Henrik Skibbe and Benjamin Drayer and Thorsten Schmidt and Alida Filippi and Roland Nitschke and Thomas Brox and Hans Burkhardt and Wolfgang Driever +Journal +Nature Methods +Year +2012 +Month +Jun +Abstract +Precise three-dimensional (3D) mapping of a large number of gene expression patterns, neuronal types and connections to an anatomical reference helps us to understand the vertebrate brain and its development. We developed the Virtual Brain Explorer (ViBE-Z), a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern; here we demonstrate its utility for mapping neurons of the dopaminergic system. The ViBE-Z database, atlas and software are provided via a web interface. +Affiliation +1] Computer Science Department, Albert-Ludwigs-University Freiburg, Freiburg, Germany. [2] BIOSS Centre for Biological Signalling Studies, Freiburg, Germany. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:11:12 -0400 +Doi +10.1038/nmeth.2076 +Language +ENG +Pii +nmeth.2076 +Pmid +22706672 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2076 + +Schneider:2012p20999 +NIH Image to ImageJ: 25 years of image analysis (article) +Author +Caroline A Schneider and Wayne S Rasband and Kevin W Eliceiri +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +671 +Month +Jun +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:12:04 -0400 +Doi +doi:10.1038/nmeth.2089 +Language +en +Rating +0 +Url +http://www.nature.com/nmeth/journal/v9/n7/full/nmeth.2089.html +Local Files + +Remote URLs +http://www.nature.com/nmeth/journal/v9/n7/full/nmeth.2089.html +http://dx.doi.org/10.1038/nmeth.2089 + +Cardona:2012p21002 +Current challenges in open-source bioimage informatics (article) +Author +Albert Cardona and Pavel Tomancak +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +661--5 +Month +Jun +Affiliation +Institute of Neuroinformatics, University of Zurich and ETH Zürich, Zürich, Switzerland. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:14:37 -0400 +Doi +10.1038/nmeth.2082 +Language +eng +Pii +nmeth.2082 +Pmid +22743770 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2082 + +Carpenter:2012p21003 +A call for bioimaging software usability (article) +Author +Anne E Carpenter and Lee Kamentsky and Kevin W Eliceiri +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +666--70 +Month +Jun +Affiliation +Imaging Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:14:50 -0400 +Doi +10.1038/nmeth.2073 +Language +eng +Pii +nmeth.2073 +Pmid +22743771 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2073 + +deChaumont:2012p21006 +Icy: an open bioimage informatics platform for extended reproducible research (article) +Author +Fabrice de Chaumont and Stéphane Dallongeville and Nicolas Chenouard and Nicolas Hervé and Sorin Pop and Thomas Provoost and Vannary Meas-Yedid and Praveen Pankajakshan and Timothée Lecomte and Yoann Le Montagner and Thibault Lagache and Alexandre Dufour and Jean-Christophe Olivo-Marin +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +690--6 +Month +Jun +Abstract +Current research in biology uses evermore complex computational and imaging tools. Here we describe Icy, a collaborative bioimage informatics platform that combines a community website for contributing and sharing tools and material, and software with a high-end visual programming framework for seamless development of sophisticated imaging workflows. Icy extends the reproducible research principles, by encouraging and facilitating the reusability, modularity, standardization and management of algorithms and protocols. Icy is free, open-source and available at http://icy.bioimageanalysis.org/. +Affiliation +Institut Pasteur, Unité d'Analyse d'Images Quantitative, Centre National de la Recherche Scientifique, Unité de Recherche Associée 2582, Paris, France. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:15:03 -0400 +Doi +10.1038/nmeth.2075 +Language +eng +Pii +nmeth.2075 +Pmid +22743774 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2075 + +Eliceiri:2012p21007 +Biological imaging software tools (article) +Author +Kevin W Eliceiri and Michael R Berthold and Ilya G Goldberg and Luis Ibáñez and B S Manjunath and Maryann E Martone and Robert F Murphy and Hanchuan Peng and Anne L Plant and Badrinath Roysam and Nico Stuurmann and Jason R Swedlow and Pavel Tomancak and Anne E Carpenter +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +697--710 +Month +Jun +Abstract +Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options. +Affiliation +Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, Wisconsin, USA. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:15:15 -0400 +Doi +10.1038/nmeth.2084 +Language +eng +Pii +nmeth.2084 +Pmid +22743775 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2084 + +Kankaanpaa:2012p21005 +BioImageXD: an open, general-purpose and high-throughput image-processing platform (article) +Author +Pasi Kankaanpää and Lassi Paavolainen and Silja Tiitta and Mikko Karjalainen and Joacim Päivärinne and Jonna Nieminen and Varpu Marjomäki and Jyrki Heino and Daniel J White +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +683--9 +Month +Jun +Abstract +BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes. We demonstrate its performance in a study of integrin clustering in response to selected inhibitors. +Affiliation +Department of Biochemistry and Food Chemistry, University of Turku, Turku, Finland. +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 10:18:40 -0400 +Doi +10.1038/nmeth.2047 +Language +eng +Pii +nmeth.2047 +Pmid +22743773 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2047 + +Schindelin:2012p21012 +Fiji: an open-source platform for biological-image analysis (article) +Author +Johannes Schindelin and Ignacio Arganda-Carreras and Erwin Frise and Verena Kaynig and Mark Longair and Tobias Pietzsch and Stephan Preibisch and Curtis Rueden and Stephan Saalfeld and Benjamin Schmid and Jean-Yves Tinevez and Daniel James White and Volker Hartenstein and Kevin Eliceiri and Pavel Tomancak and Albert Cardona +Journal +Nature Methods +Year +2012 +Volume +9 +Number +7 +Pages +676--82 +Month +Jun +Abstract +Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities. +Affiliation +1] Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. [2] Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, Wisconsin, USA (J.S.), Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany (B.S.) and Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA (S.P. and A.C.). +Date-Added +2012-07-02 16:01:24 -0400 +Date-Modified +2012-07-03 09:13:31 -0400 +Doi +10.1038/nmeth.2019 +Language +eng +Pii +nmeth.2019 +Pmid +22743772 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth.2019 + +Federici:2012p20773 +Integrated genetic and computation methods for in planta cytometry (article) +Author +Fernán Federici and Lionel Dupuy and Laurent Laplaze and Marcus Heisler and Jim Haseloff +Journal +Nature methods +Year +2012 +Month +Jun +Abstract +We present the coupled use of specifically localized fluorescent gene markers and image processing for automated quantitative analysis of cell growth and genetic activity across living plant tissues. We used fluorescent protein markers to identify cells, create seeds and boundaries for the automatic segmentation of cell geometries and ratiometrically measure gene expression cell by cell in Arabidopsis thaliana. +Affiliation +1] Department of Plant Sciences, University of Cambridge, Cambridge, UK. [2]. +Date-Added +2012-06-07 11:35:10 -0400 +Date-Modified +2012-07-03 09:14:18 -0400 +Doi +10.1038/nmeth.1940 +Language +ENG +Pii +nmeth.1940 +Pmid +22466793 +Rating +0 +Url +http://www.nature.com/nmeth/journal/v9/n5/full/nmeth.1940.html +Local Files + +Remote URLs +http://www.nature.com/nmeth/journal/v9/n5/full/nmeth.1940.html +http://dx.doi.org/10.1038/nmeth.1940 + +5540029 +Neuron geometry extraction by perceptual grouping in ssTEM images (inproceedings) +Author +Kaynig, V. and Fuchs, T. and Buhmann, J.M. +Booktitle +Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on +Year +2010 +Pages +2902 -2909 +Month +june +Keywords +automatic 3D reconstructions;cost function;dendrites;electron microscopy image segmentation;graph cut optimization;membranes;neuroanatomy;neuron geometry extraction;perceptual grouping constraint;probability output;random forest classifier;satellite imagery;ssTEM images;street segmentations;thin elongated structure segmentation;feature extraction;geometry;graph theory;image classification;image reconstruction;image segmentation;medical image processing;optimisation;probability;transmission electron microscopy; +Abstract +In the field of neuroanatomy, automatic segmentation of electron microscopy images is becoming one of the main limiting factors in getting new insights into the functional structure of the brain. We propose a novel framework for the segmentation of thin elongated structures like membranes in a neuroanatomy setting. The probability output of a random forest classifier is used in a regular cost function, which enforces gap completion via perceptual grouping constraints. The global solution is efficiently found by graph cut optimization. We demonstrate substantial qualitative and quantitative improvement over state-of the art segmentations on two considerably different stacks of ssTEM images as well as in segmentations of streets in satellite imagery. We demonstrate that the superior performance of our method yields fully automatic 3D reconstructions of dendrites from ssTEM data. +Date-Added +2012-06-07 11:31:44 -0400 +Date-Modified +2012-06-07 11:31:44 -0400 +Doi +10.1109/CVPR.2010.5540029 +Issn +1063-6919 +Local Files +Remote URLs +http://dx.doi.org/10.1109/CVPR.2010.5540029 + +Saalfeld:2010p20772 +As-rigid-as-possible mosaicking and serial section registration of large ssTEM datasets (article) +Author +Stephan Saalfeld and Albert Cardona and Volker Hartenstein and Pavel Tomancák +Journal +Bioinformatics +Year +2010 +Volume +26 +Number +12 +Pages +i57--63 +Month +Jun +Keywords +Imaging: Three-Dimensional, Animals, Microscopy: Electron: Transmission, Databases: Factual, Drosophila +Abstract +MOTIVATION: Tiled serial section Transmission Electron Microscopy (ssTEM) is increasingly used to describe high-resolution anatomy of large biological specimens. In particular in neurobiology, TEM is indispensable for analysis of synaptic connectivity in the brain. Registration of ssTEM image mosaics has to recover the 3D continuity and geometrical properties of the specimen in presence of various distortions that are applied to the tissue during sectioning, staining and imaging. These include staining artifacts, mechanical deformation, missing sections and the fact that structures may appear dissimilar in consecutive sections. + +RESULTS: We developed a fully automatic, non-rigid but as-rigid-as-possible registration method for large tiled serial section microscopy stacks. We use the Scale Invariant Feature Transform (SIFT) to identify corresponding landmarks within and across sections and globally optimize the pose of all tiles in terms of least square displacement of these landmark correspondences. We evaluate the precision of the approach using an artificially generated dataset designed to mimic the properties of TEM data. We demonstrate the performance of our method by registering an ssTEM dataset of the first instar larval brain of Drosophila melanogaster consisting of 6885 images. + +AVAILABILITY: This method is implemented as part of the open source software TrakEM2 (http://www.ini.uzh.ch/~acardona/trakem2.html) and distributed through the Fiji project (http://pacific.mpi-cbg.de). +Affiliation +Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. +Date-Added +2012-06-07 11:27:59 -0400 +Date-Modified +2012-06-07 11:27:59 -0400 +Doi +10.1093/bioinformatics/btq219 +Language +eng +Pii +btq219 +Pmid +20529937 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1093/bioinformatics/btq219 + +Cardona:2009p20772 +Drosophila brain development: closing the gap between a macroarchitectural and microarchitectural approach (article) +Author +A Cardona and S Saalfeld and P Tomancak and V Hartenstein +Journal +Cold Spring Harbor Symposia on Quantitative Biology +Year +2009 +Volume +74 +Pages +235--48 +Month +Jan +Keywords +Imaging: Three-Dimensional, Microscopy: Electron: Transmission, Nerve Net, Brain, Models: Neurological, Animals, Phylogeny, Cell Lineage, Neurites, Drosophila, Synapses, Larva, Animals: Genetically Modified, Species Specificity, Neuropil, Mice +Abstract +Neurobiologists address neural structure, development, and function at the level of "macrocircuits" (how different brain compartments are interconnected; what overall pattern of activity they produce) and at the level of "microcircuits" (how connectivity and physiology of individual neurons and their processes within a compartment determine the functional output of this compartment). Work in our lab aims at reconstructing the developing Drosophila brain at both levels. Macrocircuits can be approached conveniently by reconstructing the pattern of brain lineages, which form groups of neurons whose projections form cohesive fascicles interconnecting the compartments of the larval and adult brain. The reconstruction of microcircuits requires serial section electron microscopy, due to the small size of terminal neuronal processes and their synaptic contacts. Because of the amount of labor that traditionally comes with this approach, very little is known about microcircuitry in brains across the animal kingdom. Many of the problems of serial electron microscopy reconstruction are now solvable with digital image recording and specialized software for both image acquisition and postprocessing. In this chapter, we introduce our efforts to reconstruct the small Drosophila larval brain and discuss our results in light of the published data on neuropile ultrastructure in other animal taxa. +Affiliation +Department of Molecular, Cell, and Developmental Biology, University of California at Los Angeles, Los Angeles, CA 90095, USA. +Date-Added +2012-06-07 11:24:27 -0400 +Date-Modified +2012-06-07 11:24:27 -0400 +Doi +10.1101/sqb.2009.74.037 +Language +eng +Pii +sqb.2009.74.037 +Pmid +20028843 +Rating +0 +Local Files + +Remote URLs +http://dx.doi.org/10.1101/sqb.2009.74.037 + +Preibisch:2010p20771 +Software for bead-based registration of selective plane illumination microscopy data (article) +Author +Stephan Preibisch and Stephan Saalfeld and Johannes Schindelin and Pavel Tomancak +Journal +Nature Methods +Year +2010 +Volume +7 +Number +6 +Pages +418--9 +Month +Jun +Keywords +Drosophila melanogaster, Caenorhabditis elegans, Imaging: Three-Dimensional, Software, Lighting, Animals, Microscopy +Date-Added +2012-06-07 07:57:11 -0400 +Date-Modified +2012-06-07 07:57:11 -0400 +Doi +10.1038/nmeth0610-418 +Language +eng +Pii +nmeth0610-418 +Pmid +20508634 +Rating +0 +Uri +papers://B79267E9-EE15-4C9F-820C-6D298DF1DC27/Paper/p20771 +Local Files + +Remote URLs +http://dx.doi.org/10.1038/nmeth0610-418 + +Longair:2011p20768 +Simple Neurite Tracer: open source software for reconstruction, visualization and analysis of neuronal processes (article) +Author +Mark H Longair and Dean A Baker and J Douglas Armstrong +Journal +Bioinformatics +Year +2011 +Volume +27 +Number +17 +Pages +2453--4 +Month +Sep +Keywords +Neurons, Animals, Computer Graphics, Imaging: Three-Dimensional, Neurites, Software, Image Processing: Computer-Assisted, Humans +Abstract +MOTIVATION: Advances in techniques to sparsely label neurons unlock the potential to reconstruct connectivity from 3D image stacks acquired by light microscopy. We present an application for semi-automated tracing of neurons to quickly annotate noisy datasets and construct complex neuronal topologies, which we call the Simple Neurite Tracer. AVAILABILITY: Simple Neurite Tracer is open source software, licensed under the GNU General Public Licence (GPL) and based on the public domain image processing software ImageJ. The software and further documentation are available via http://fiji.sc/Simple_Neurite_Tracer as part of the package Fiji, and can be used on Windows, Mac OS and Linux. Documentation and introductory screencasts are available at the same URL. CONTACT: longair@ini.phys.ethz.ch; longair@ini.phys.ethz.ch. +Affiliation +Institute of Neuroinformatics, Uni/ETH Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland. longair@ini.phys.ethz.ch +Date-Added +2012-05-30 15:50:35 -0400 +Date-Modified +2012-06-07 10:02:23 -0400 +Doi +10.1093/bioinformatics/btr390 +Language +eng +Pii +btr390 +Pmid +21727141 +Rating +0 +Local Files +~/Documents/Papers/Armstrong Bioinformatics 2011.pdf +Remote URLs +http://bioinformatics.oxfordjournals.org/content/27/17/2453.long +http://dx.doi.org/10.1093/bioinformatics/btr390 + +Leymarie199284 +Fast raster scan distance propagation on the discrete rectangular lattice (article) +Author +F. Leymarie and M. D. Levine +Journal +CVGIP: Image Understanding +Year +1992 +Volume +55 +Number +1 +Pages +84--94 +Date-Added +2011-08-02 16:51:26 -0400 +Date-Modified +2011-10-27 09:35:14 -0400 +Doi +DOI: 10.1016/1049-9660(92)90008-Q +Issn +1049-9660 +Local Files +Remote URLs +http://dx.doi.org/10.1016/1049-9660(92)90008-Q + +Henriques:2010vn +QuickPALM: 3D real-time photoactivation nanoscopy image processing in ImageJ (article) +Author +Henriques, Ricardo and Lelek, Mickael and Fornasiero, Eugenio F and Valtorta, Flavia and Zimmer, Christophe and Mhlanga, Musa M +Journal +Nat Methods +Year +2010 +Volume +7 +Number +5 +Pages +339-40 +Month +May +Date-Added +2011-07-26 14:51:54 -0400 +Date-Modified +2011-07-26 14:53:28 -0400 +Doi +10.1038/nmeth0510-339 +Journal-Full +Nature methods +Mesh +Animals; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Mice; Microscopy; Microtubules; Software +Pmid +20431545 +Pst +ppublish +Local Files +Remote URLs +http://dx.doi.org/10.1038/nmeth0510-339 + +Fischer:2010kx +Measurement of meningeal blood vessel diameter in vivo with a plug-in for ImageJ (article) +Author +Fischer, Michael J M and Uchida, Sae and Messlinger, Karl +Journal +Microvasc Res +Year +2010 +Volume +80 +Number +2 +Pages +258-66 +Month +Sep +Abstract +Changes in blood vessel diameter can be measured manually, but this is time-consuming and often impractical. For automatic measurement commercial solutions are available, but the proprietary algorithms and their potential shortcomings are not known to the user. We present an approach with a CCD camera for image acquisition combined with free and open source ImageJ software for offline analysis. A subtraction image allows for the evaluation of the diameter changes throughout the field of view. A full width at half-maximum algorithm plug-in was written to measure the vessel diameter. For a given line across a vessel, the results of five measurements with parallel shifts throughout an image stack are copied to the clipboard. For validation of this method an established in vivo model was used, namely vascular changes in the rat dura mater, reflecting the activity of the afferent neurons. Vasoconstriction of the meningeal arterioles induced by local electrical stimulation of the dura was inhibited by intravenous administration of the adrenoceptor antagonist phentolamine and amplified by the CGRP receptor antagonist olcegepant. The described methods allow the user to quickly evaluate vessel diameter changes in the whole acquired field at any selected position. +Date-Added +2011-07-26 14:51:31 -0400 +Date-Modified +2011-07-26 14:53:16 -0400 +Doi +10.1016/j.mvr.2010.04.004 +Journal-Full +Microvascular research +Mesh +Algorithms; Animals; Antihypertensive Agents; Arterioles; Dipeptides; Dura Mater; Electric Stimulation; Image Processing, Computer-Assisted; Injections, Intravenous; Microscopy, Video; Phentolamine; Quinazolines; Rats; Rats, Wistar; Software; Vasoconstriction +Pmid +20406650 +Pst +ppublish +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.mvr.2010.04.004 + +Andrews:2010uq +Difference Tracker: ImageJ plugins for fully automated analysis of multiple axonal transport parameters (article) +Author +Andrews, Simon and Gilley, Jonathan and Coleman, Michael P +Journal +J Neurosci Methods +Year +2010 +Volume +193 +Number +2 +Pages +281-7 +Month +Nov +Abstract +Studies of axonal transport are critical, not only to understand its normal regulation, but also to determine the roles of transport impairment in disease. Exciting new resources have recently become available allowing live imaging of axonal transport in physiologically relevant settings, such as mammalian nerves. Thus the effects of disease, ageing and therapies can now be assessed directly in nervous system tissue. However, these imaging studies present new challenges. Manual or semi-automated analysis of the range of transport parameters required for a suitably complete evaluation is very time-consuming and can be subjective due to the complexity of the particle movements in axons in ex vivo explants or in vivo. We have developed Difference Tracker, a program combining two new plugins for the ImageJ image-analysis freeware, to provide fast, fully automated and objective analysis of a number of relevant measures of trafficking of fluorescently labeled particles so that axonal transport in different situations can be easily compared. We confirm that Difference Tracker can accurately track moving particles in highly simplified, artificial simulations. It can also identify and track multiple motile fluorescently labeled mitochondria simultaneously in time-lapse image stacks from live imaging of tibial nerve axons, reporting values for a number of parameters that are comparable to those obtained through manual analysis of the same axons. Difference Tracker therefore represents a useful free resource for the comparative analysis of axonal transport under different conditions, and could potentially be used and developed further in many other studies requiring quantification of particle movements. +Date-Added +2011-07-26 14:51:15 -0400 +Date-Modified +2011-07-26 14:52:57 -0400 +Doi +10.1016/j.jneumeth.2010.09.007 +Journal-Full +Journal of neuroscience methods +Mesh +Animals; Automatic Data Processing; Axonal Transport; Axons; Green Fluorescent Proteins; Mice; Mice, Transgenic; Microscopy, Confocal; Mitochondria; Organ Culture Techniques; Software; Statistics, Nonparametric; Tibial Nerve; Time Factors +Pmid +20869987 +Pst +ppublish +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jneumeth.2010.09.007 + +Kriston-Vizi:2011fk +Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3d segmentation algorithms (article) +Author +Kriston-Vizi, Janos and Thong, Ng Wee and Poh, Cheok Leong and Yee, Kwo Chia and Ling, Joan Sim Poh and Kraut, Rachel and Wasser, Martin +Journal +BMC Bioinformatics +Year +2011 +Volume +12 +Pages +232 +Abstract +ABSTRACT: +Date-Added +2011-07-26 14:50:36 -0400 +Date-Modified +2011-07-26 14:50:36 -0400 +Doi +10.1186/1471-2105-12-232 +Journal-Full +BMC bioinformatics +Pmid +21668958 +Pst +epublish +Local Files +Remote URLs +http://dx.doi.org/10.1186/1471-2105-12-232 + +Edelstein:2010p18714 +Computer control of microscopes using \microManager (article) +Author +Arthur Edelstein and Nenad Amodaj and Karl Hoover and Ron Vale and Nico Stuurman +Journal +Curr Protoc Mol Biol +Year +2010 +Volume +Chapter 14 +Pages +Unit14.20 +Month +Oct +Abstract +With the advent of digital cameras and motorization of mechanical components, computer control of microscopes has become increasingly important. Software for microscope image acquisition should not only be easy to use, but also enable and encourage novel approaches. The open-source software package µManager aims to fulfill those goals. This unit provides step-by-step protocols describing how to get started working with µManager, as well as some starting points for advanced use of the software. +Affiliation +Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California, USA. +Date-Added +2010-12-27 19:19:56 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/0471142727.mb1420s92 +Language +eng +Pmid +20890901 +Rating +0 +Local Files +Remote URLs +http://onlinelibrary.wiley.com/doi/10.1002/0471142727.mb1420s92/abstract;jsessionid=2210B52A543C0033B6389AEF72232BE8.d03t02 +http://dx.doi.org/10.1002/0471142727.mb1420s92 + +Doube:2010p18704 +BoneJ: Free and extensible bone image analysis in ImageJ (article) +Author +Michael Doube and Michal M Klosowski and Ignacio Arganda-Carreras and Fabrice P Cordelieres and Robert P Dougherty and Jonathan S Jackson and Benjamin Schmid and John R Hutchinson and Sandra J Shefelbine +Journal +Bone +Year +2010 +Volume +47 +Number +6 +Pages +1076--9 +Month +Dec +Abstract +Bone geometry is commonly measured on computed tomographic (CT) and X-ray microtomographic (μCT) images. We obtained hundreds of CT, μCT and synchrotron μCT images of bones from diverse species that needed to be analysed remote from scanning hardware, but found that available software solutions were expensive, inflexible or methodologically opaque. We implemented standard bone measurements in a novel ImageJ plugin, BoneJ, with which we analysed trabecular bone, whole bones and osteocyte lacunae. BoneJ is open source and free for anyone to download, use, modify and distribute. +Affiliation +Department of Bioengineering, Imperial College London, South Kensington, London SW7 2AZ, UK. m.doube@imperial.ac.uk +Date-Added +2010-12-27 11:24:22 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.bone.2010.08.023 +Language +eng +Pii +S8756-3282(10)01441-9 +Pmid +20817052 +Rating +0 +Local Files +~/Documents/Papers/Shefelbine Bone 2010.pdf +Remote URLs +http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T4Y-50XV9CV-2&_user=458507&_coverDate=12%252F31%252F2010&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_acct=C000022002&_version=1&_urlVersion=0&_userid=458507&md5=1b0702d1c33e30274b9a96f3bc854bae&searchtype=a +http://dx.doi.org/10.1016/j.bone.2010.08.023 + +Landini:2009p19625 +Digital enhancement of haematoxylin- and eosin-stained histological images for red-green colour-blind observers (article) +Author +G Landini and G Perryer +Journal +J Microsc +Year +2009 +Volume +234 +Number +3 +Pages +293--301 +Month +Jun +Keywords +Color Vision Defects, Image Enhancement, Histocytochemistry, Humans +Abstract +Individuals with red-green colour-blindness (CB) commonly experience great difficulty differentiating between certain histological stain pairs, notably haematoxylin-eosin (HE). The prevalence of red-green CB is high (6-10% of males), including among medical and laboratory personnel, and raises two major concerns: first, accessibility and equity issues during the education and training of individuals with this disability, and second, the likelihood of errors in critical tasks such as interpreting histological images. Here we show two methods to enhance images of HE-stained samples so the differently stained tissues can be well discriminated by red-green CBs while remaining usable by people with normal vision. Method 1 involves rotating and stretching the range of HE hues in the image to span the perceptual range of the CB observers. Method 2 digitally unmixes the original dyes using colour deconvolution into two separate images and repositions the information into hues that are more distinctly perceived. The benefits of these methods were tested in 36 volunteers with normal vision and 11 with red-green CB using a variety of HE stained tissue sections paired with their enhanced versions. CB subjects reported they could better perceive the different stains using the enhanced images for 85% of preparations (method 1: 90%, method 2: 73%), compared to the HE-stained original images. Many subjects with normal vision also preferred the enhanced images to the original HE. The results suggest that these colour manipulations confer considerable advantage for those with red-green colour vision deficiency while not disadvantaging people with normal colour vision. +Affiliation +Oral Pathology Unit, School of Dentistry, College of Medical and Dental Sciences, University of Birmingham, St. Chad's Queensway, Birmingham B46NN, UK +Date-Added +2011-07-01 15:12:59 -0400 +Date-Modified +2011-07-06 22:23:39 -0400 +Doi +10.1111/j.1365-2818.2009.03174.x +Language +eng +Pii +JMI3174 +Pmid +19493108 +Rating +0 +Local Files +~/Documents/Papers/Perryer J Microsc 2009.pdf +Remote URLs +http://dx.doi.org/10.1111/j.1365-2818.2009.03174.x + +Schmid:2010p18702 +A high-level 3D visualization API for Java and ImageJ (article) +Author +Benjamin Schmid and Johannes Schindelin and Albert Cardona and Mark Longair and Martin Heisenberg +Journal +BMC Bioinformatics 2010 11:274 +Year +2010 +Volume +11 +Pages +274 +Month +Jan +Keywords +Microscopy: Confocal, Software, Programming Languages, Imaging: Three-Dimensional, Pattern Recognition: Automated, Computer Graphics, Image Interpretation: Computer-Assisted +Abstract +Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de. +Affiliation +Department of Neurobiology and Genetics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. b.schmid@biozentrum.uni-wuerzburg.de +Date-Added +2010-12-27 11:19:50 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1471-2105-11-274 +Language +eng +Pii +1471-2105-11-274 +Pmid +20492697 +Rating +0 +Local Files +~/Documents/Papers/Heisenberg BMC Bioinformatics 2010.pdf +Remote URLs +http://dx.doi.org/10.1186/1471-2105-11-274 + +Cardona:2010p18306 +An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy (article) +Author +Albert Cardona and Stephan Saalfeld and Stephan Preibisch and Benjamin Schmid and Anchi Cheng and Jim Pulokas and Pavel Tomancak and Volker Hartenstein +Journal +PLoS Biol +Year +2010 +Volume +8 +Number +10 +Month +Jan +Abstract +The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile. +Affiliation +Institute of Neuroinformatics, ETH/University of Zürich, Zürich, Switzerland. +Date-Added +2010-12-27 11:18:57 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1371/journal.pbio.1000502 +Language +eng +Pmid +20957184 +Rating +0 +Local Files +~/Documents/Papers/Hartenstein PLoS Biol 2010.pdf +Remote URLs +http://dx.doi.org/10.1371/journal.pbio.1000502 + +Carpenter:2006p1986 +CellProfiler: image analysis software for identifying and quantifying cell phenotypes (article) +Author +Anne E Carpenter and Thouis R Jones and Michael R Lamprecht and Colin Clarke and In Han Kang and Ola Friman and David A Guertin and Joo Han Chang and Robert A Lindquist and Jason Moffat and Polina Golland and David M Sabatini +Journal +Genome Biol +Year +2006 +Volume +7 +Number +10 +Pages +R100 +Month +Dec +Keywords +Dose-Response Relationship, Drug, Models, Genetic, Image Processing, Computer-Assisted, Software, Phenotype, Mutation, Reproducibility of Results, Gene Expression Profiling +Abstract +ABSTRACT : Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining). +Affiliation +Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA. +Date-Added +2010-12-23 11:00:27 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/gb-2006-7-10-r100 +Language +English +Pii +gb-2006-7-10-r100 +Pmid +17076895 +Rating +0 +Local Files +~/Documents/Papers/Sabatini Genome Biol 2006.pdf +Remote URLs +http://dx.doi.org/10.1186/gb-2006-7-10-r100 + +Walter:2010p16649 +Visualization of image data from cells to organisms (article) +Author +Thomas Walter and David W Shattuck and Richard Baldock and Mark E Bastin and Anne E Carpenter and Suzanne Duce and Jan Ellenberg and Adam Fraser and Nicholas Hamilton and Steve Pieper and Mark A Ragan and Jurgen E Schneider and Pavel Tomancak and Jean-Karim Hériché +Journal +Nature Methods +Year +2010 +Volume +7 +Number +3 Suppl +Pages +S26--41 +Month +Mar +Abstract +Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges. +Affiliation +European Molecular Biology Laboratory, Heidelberg, Germany. +Date-Added +2010-03-23 02:38:52 -0400 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1038/nmeth.1431 +Language +eng +Pii +nmeth.1431 +Pmid +20195255 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1038/nmeth.1431 + +Bailer:2006p14110 +Writing ImageJ Plugins--A Tutorial (article) +Author +W Bailer +Journal +Upper Austria University of Applied Sciences Dept. of Media Technology and Design Hagenberg, Austria, \url{http://www.gm.fh-koeln.de/~konen/WPF-BV/tutorial-ImageJ_V1.71.pdf} +Year +2006 +Month +Jan +Abstract +∗The author is now with the Institute of Information Systems and Information Management at Joanneum Research GmbH. in Graz, Austria. †This document can be downloaded from www.fh-hagenberg.at/mtd/depot/imaging/ ‡Fachhochschule Hagenberg, +Date-Added +2010-01-30 07:53:31 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Rating +0 +Local Files +~/Documents/Papers/Hagenberg Upper Austria University of Applied … 2006.pdf +Remote URLs +http://www.gm.fh-koeln.de/~konen/WPF-BV/tutorial-ImageJ_V1.71.pdf + +Ferrer:2004p14287 +A new ImageJ plugin to correct for partial effect volume (article) +Author +L Ferrer and Y Grealou and D Autret and S Gaudaire and G Brunet and G Delpon and A Lisbona and B Bridji and I Resche and C Rousseau and T Carlier and M BardiAs +Journal +Eur J Nucl Med Mol I +Year +2004 +Volume +31 +Pages +S230--S230 +Month +Jan +Affiliation +RenA Gauducheau Canc Ctr, Dept Med Phys, St Herblain, France +Date-Added +2010-01-30 07:46:38 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +English +Pmid +000223419900134 +Rating +0 +Local Files +Remote URLs + +Carlier:2005p14017 +Quality controls for gamma cameras and PET cameras: development of a free open-source ImageJ program (article) +Author +Thomas Carlier and Ludovic Ferrer and Jean B Berruchon and Regis Cuissard and Adeline Martineau and Pierre Loonis and Olivier Couturier +Journal +Medical Imaging 2005: Physics of Medical Imaging. Edited by Flynn +Year +2005 +Volume +5745 +Pages +1237 +Month +Apr +Abstract +Acquisition data and treatments for quality controls of gamma cameras and Positron Emission Tomography (PET) cameras are commonly performed with dedicated program packages, which are running only on manufactured computers and differ from each other, depending on camera company and program versions. The aim of this work was to develop a free open-source program (written in JAVA language) to analyze data for quality control of gamma cameras and PET cameras. The program is based on the free application software ImageJ and can be easily loaded on any computer operating system (OS) and thus on any type of computer in every nuclear medicine department. Based on standard parameters of quality control, this program includes 1) for gamma camera: a rotation center control (extracted from the American Association of Physics in Medicine, AAPM, norms) and two uniformity controls (extracted from the Institute of Physics and Engineering in Medicine, IPEM, and National Electronic Manufacturers Association, NEMA, norms). 2) For PET systems, three quality controls recently defined by the French Medical Physicist Society (SFPM), i.e. spatial resolution and uniformity in a reconstructed slice and scatter fraction, are included. The determination of spatial resolution (thanks to the Point Spread Function, PSF, acquisition) allows to compute the Modulation Transfer Function (MTF) in both modalities of cameras. All the control functions are included in a tool box which is a free ImageJ plugin and could be soon downloaded from Internet. Besides, this program offers the possibility to save on HTML format the uniformity quality control results and a warning can be set to automatically inform users in case of abnormal results. The architecture of the program allows users to easily add any other specific quality control program. Finally, this toolkit is an easy and robust tool to perform quality control on gamma cameras and PET cameras based on standard computation parameters, is free, run on any type of computer and will soon be downloadable from the net (http://rsb.info.nih.gov/ij/plugins or http://nucleartoolkit.free.fr). +Affiliation +AA(Univ. Hospital/Nantes (France)), AB(R. Gauducheau Cancer Ctr. (France)), AC(Univ. of La Rochelle (France)), AD(Univ. of La Rochelle (France)), AE(Univ. of La Rochelle (France)), AF(Univ. of La Rochelle (France)), AG(Univ. Hospital/Nantes (France) and INSERM (France)) +Annote +(c) 2005: SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. +Date-Added +2010-01-30 07:45:55 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1117/12.595539 +Pmid +2005SPIE.5745.1237C +Rating +0 +Local Files +Remote URLs +http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005SPIE.5745.1237C&link_type=ABSTRACT +http://dx.doi.org/10.1117/12.595539 + +Igathinathane:2009p14264 +Major orthogonal dimensions measurement of food grains by machine vision using ImageJ (article) +Author +C Igathinathane and LO Pordesimo and WD Batchelor +Journal +Food Res Int +Year +2009 +Volume +42 +Number +1 +Pages +76--84 +Month +Jan +Keywords +Shape, Physical Property, Image Processing, Dimension, Size Distribution, Food Grain, Color, Machine Vision, Identification, System, Wheat +Abstract +A machine vision ImageJ plugin was developed in Java for orthogonal length and width determination of singulated particles from digital images. A flatbed scanner obtained the digital images of particulate samples. The "pixel-march" method, which compared pixel colors to determine object boundaries for dimensional measurements, utilized only the ImageJ fitted-ellipse centroid coordinates and major axis inclination. The pixel-march started from objects centroid and proceeded along the fitted-ellipses' major and minor axes for boundary identification. Actual dimensions of selected reference particles measured using digital calipers validated the plugin. The plugin was applied to measure orthogonal dimensions of eight types of food grains. The plugin has overall accuracy greater than 96.6%, computation speed of 254 +/- 125 particles/s, handles all shapes and particle orientations, makes repeatable measurements, and is economical. Applications of developed plugin may include routine laboratory dimensional measurements, physical dimensional characteristics, size based grading, and sieve analysis simulation for particle size distribution. Published by Elsevier Ltd. +Affiliation +Mississippi State Univ, Dept Agr {\&} Biol Engn, Mississippi State, MS 39762 USA +Date-Added +2010-01-30 07:45:32 -0500 +Date-Modified +2011-07-06 15:22:18 -0400 +Doi +10.1016/j.foodres.2008.08.013 +Language +English +Pmid +000263215300010 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.foodres.2008.08.013 + +Moodley:2004p14284 +A colour-map plugin for the open source, Java based, image processing package, ImageJ (article) +Author +K Moodley and H Murrell +Journal +Computers {\&} Geosciences +Year +2004 +Volume +30 +Number +6 +Pages +609--618 +Month +Jan +Keywords +Colour Models, Interpolation, Image Enhancement, Greyscale, Pseudo-Colouring +Abstract +We present an interactive approach to the pseudo-colouring of greyscale images. We implement the technique by computing mappings from a three-dimensional (3D) colour space to a one-dimensional greyscale space (i.e. R-3 to R). To compute our maps, we employ both linear and nonlinear interpolation in 3D colour space. We validate our work by applying our maps to greyscale images resulting in significant image enhancement. Applications include space imagery, geological topographies, medical scans and many more. Our tool is coded as a Java plug-in for the open source image processing package, ImageJ. (C) 2004 Elsevier Ltd. All rights reserved. +Affiliation +Univ Natal, Dept Comp Sci, ZA-40413 Durban, South Africa +Date-Added +2010-01-30 07:45:05 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.cageo.2004.03.017 +Language +English +Pmid +000223097300006 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.cageo.2004.03.017 + +Schartz:2007p14035 +WorkstationJ: workstation emulation software for medical image perception and technology evaluation research (article) +Author +Kevin M Schartz and Kevin S Berbaum and Robert T Caldwell and Mark T Madsen +Journal +Medical Imaging 2007: Image Perception +Year +2007 +Volume +6515 +Pages +49 +Month +Mar +Abstract +We developed image presentation software that mimics the functionality available in the clinic, but also records time-stamped, observer-display interactions and is readily deployable on diverse workstations making it possible to collect comparable observer data at multiple sites. Commercial image presentation software for clinical use has limited application for research on image perception, ergonomics, computer-aids and informatics because it does not collect observer responses, or other information on observer-display interactions, in real time. It is also very difficult to collect observer data from multiple institutions unless the same commercial software is available at different sites. Our software not only records observer reports of abnormalities and their locations, but also inspection time until report, inspection time for each computed radiograph and for each slice of tomographic studies, window/level, and magnification settings used by the observer. The software is a modified version of the open source ImageJ software available from the National Institutes of Health. Our software involves changes to the base code and extensive new plugin code. Our free software is currently capable of displaying computed tomography and computed radiography images. The software is packaged as Java class files and can be used on Windows, Linux, or Mac systems. By deploying our software together with experiment-specific script files that administer experimental procedures and image file handling, multi-institutional studies can be conducted that increase reader and/or case sample sizes or add experimental conditions. +Affiliation +AA(Univ. of Iowa (USA)), AB(Univ. of Iowa (USA)), AC(Univ. of Iowa (USA)), AD(Univ. of Iowa (USA)) +Annote +(c) 2007: SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. +Date-Added +2010-01-30 07:44:30 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1117/12.708482 +Pmid +2007SPIE.6515E..49S +Rating +0 +Local Files +Remote URLs +http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007SPIE.6515E..49S&link_type=ABSTRACT +http://dx.doi.org/10.1117/12.708482 + +Ma:2006uq +Quantifying the intercellular forces during Drosophila morphogenesis (article) +Author +XMa and MSHutson +Journal +American Physical Society +Year +2006 +Pages +29003 +Month +Mar +Date-Added +2010-01-30 07:35:43 -0500 +Date-Modified +2012-06-07 10:09:50 -0400 +Url +http://meetings.aps.org/link/BAPS.2006.MAR.H29.3 +Local Files +Remote URLs +http://meetings.aps.org/link/BAPS.2006.MAR.H29.3 + +Meijering:2004p1104 +Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. (article) +Author +E Meijering and M Jacob and J-C F Sarria and P Steiner and H Hirling and M Unser +Journal +Cytometry. Part A : the journal of the International Society for Analytical Cytology +Year +2004 +Volume +58 +Number +2 +Pages +167--76 +Month +Apr +Keywords +Reproducibility of Results, Rats, Cells, Cultured, Hippocampus, PC12 Cells, Sensitivity and Specificity, Cell Shape, Microscopy, Fluorescence +Abstract +BACKGROUND: For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique. METHODS: The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy images of cells in culture, using both methods. Accuracy and reproducibility were determined by comparing the tracings to high-resolution reference tracings, using two error measures. Labor intensiveness was measured in numbers of mouse clicks required. The significance of the results was determined by a Student t-test and by analysis of variance. RESULTS: Both methods slightly underestimated the true neurite length, but the differences were not unanimously significant. The average deviation from the true neurite centerline was a factor 2.6 smaller with the developed technique compared to fully manual tracing. Intraobserver variability in the respective measures was reduced by a factor 6.0 and 23.2. Interobserver variability was reduced by a factor 2.4 and 8.8, respectively, and labor intensiveness by a factor 3.3. CONCLUSIONS: Providing similar accuracy in measuring neurite length, significantly improved accuracy in neurite centerline extraction, and significantly improved reproducibility and reduced labor intensiveness, the developed technique may replace fully manual tracing methods. +Affiliation +Department of Medical Informatics, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. meijering@imagescience.org +Date-Added +2010-01-29 11:59:15 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/cyto.a.20022 +Language +English +Pmid +15057970 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/cyto.a.20022 + +West:2006p15599 +Using the medical image processing package, ImageJ, for astronomy (article) +Author +Jennifer L West and Ian D Cameron +Journal +arXiv +Year +2006 +Volume +astro-ph +Month +Jan +Keywords +astro-ph +Abstract +At the most fundamental level, all digital images are just large arrays of numbers that can easily be manipulated by computer software. Specialized digital imaging software packages often use routines common to many different applications and fields of study. The freely available, platform independent, image-processing package ImageJ has many such functions. We highlight ImageJ's capabilities by presenting methods of processing sequences of images to produce a star trail image and a single high quality planetary image. +Annote +Published in: J.Roy.Astron.Soc.Canada100:242-248,2006 +Date-Added +2010-01-29 11:54:12 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Eprint +astro-ph/0611686v1 +Pmid +astro-ph/0611686v1 +Rating +0 +Local Files +Remote URLs +http://arxiv.org/abs/astro-ph/0611686v1 + +Messaoudii:2007p14007 +TomoJ: tomography software for three-dimensional reconstruction in transmission electron microscopy (article) +Author +Cédric Messaoudii and Thomas Boudier and Carlos Oscar Sanchez Sorzano and Sergio Marco +Journal +BMC Bioinformatics +Year +2007 +Volume +8 +Pages +288 +Month +Jan +Keywords +Microscopy: Electron: Transmission, Imaging: Three-Dimensional, Software, Image Interpretation: Computer-Assisted, Sensitivity and Specificity, Reproducibility of Results, Tomography: Optical, Algorithms, Image Enhancement +Abstract +BACKGROUND: Transmission electron tomography is an increasingly common three-dimensional electron microscopy approach that can provide new insights into the structure of subcellular components. Transmission electron tomography fills the gap between high resolution structural methods (X-ray diffraction or nuclear magnetic resonance) and optical microscopy. We developed new software for transmission electron tomography, TomoJ. TomoJ is a plug-in for the now standard image analysis and processing software for optical microscopy, ImageJ. RESULTS: TomoJ provides a user-friendly interface for alignment, reconstruction, and combination of multiple tomographic volumes and includes the most recent algorithms for volume reconstructions used in three-dimensional electron microscopy (the algebraic reconstruction technique and simultaneous iterative reconstruction technique) as well as the commonly used approach of weighted back-projection. CONCLUSION: The software presented in this work is specifically designed for electron tomography. It has been written in Java as a plug-in for ImageJ and is distributed as freeware. +Affiliation +Institut Curie, Section Recherche, Laboratoire d'Imagerie Intégrative, Centre Universitaire d'Orsay, 91405 Orsay CEDEX, France. cedric.messaoudi@curie.u-psud.fr +Date-Added +2010-01-19 09:17:00 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1471-2105-8-288 +Language +eng +Pii +1471-2105-8-288 +Pmid +17683598 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1186/1471-2105-8-288 + +Sieuwerts:2008p14980 +A simple and fast method for determining colony forming units (article) +Author +S Sieuwerts and FAM de Bok and E Mols and WM de Vos and JETvan Hylckama Vlieg +Journal +Lett Appl Microbiol +Year +2008 +Volume +47 +Number +4 +Pages +275--278 +Month +Jan +Keywords +Escherichia Coli, Colony Forming Units, Wine, Probes, Saccharomyces Cerevisiae, Faster Enumeration, Lactic-Acid Bacteria, Lactic Acid Bacteria, Plating, Plate Method +Abstract +Aims: To develop a flexible and fast colony forming unit quantification method that can be operated in a standard microbiology laboratory.Methods and Results: A miniaturized plating method is reported where droplets of bacterial cultures are spotted on agar plates. Subsequently, minicolony spots are imaged with a digital camera and quantified using a dedicated plug-in developed for the freeware program IMAGEJ. A comparison between conventional and minicolony plating of industrial micro-organisms including lactic acid bacteria, Eschericha coli and Saccharomyces cerevisiae showed that there was no significant difference in the results obtained with the methods.Conclusions: The presented method allows downscaling of plating by 100-fold, is flexible, easy-to-use and is more labour-efficient and cost-efficient than conventional plating methods.Significance and Impact of the Study: The method can be used for rapid assessment of viable counts of micro-organisms similar to conventional plating using standard laboratory equipment. It is faster and cheaper than conventional plating methods. +Affiliation +Nizo Food Res, NL-6710 BA Ede, Netherlands +Date-Added +2010-01-29 10:52:14 -0500 +Date-Modified +2011-07-06 15:22:18 -0400 +Doi +10.1111/j.1472-765X.2008.02417.x +Language +English +Pmid +000259362300008 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1472-765X.2008.02417.x + +Carmona:2007p14000 +A simple technique of image analysis for specific nuclear immunolocalization of proteins (article) +Author +R Carmona and D Macías and J A Guadix and V Portillo and J M Pérez-Pomares and R Muñoz-Chápuli +Journal +Journal of microscopy +Year +2007 +Volume +225 +Number +Pt 1 +Pages +96--9 +Month +Jan +Keywords +Microscopy: Confocal, Mice, Hepatocyte Nuclear Factor 1, Proliferating Cell Nuclear Antigen, Endocardium, Transcription Factors, Animals, Nuclear Proteins, Chick Embryo, Immunohistochemistry, Image Processing: Computer-Assisted, Antibodies: Monoclonal, beta Catenin +Abstract +Colocalization of fluorescent signals in confocal microscopy is usually evaluated by inspecting merged images from different colour channels or by using commercially available software packages. We describe in this paper a simple method for assessment of nuclear localization of proteins in tissue sections through confocal immunolocalization, propidium iodide counterstaining and image analysis. Through a macro command developed for the public domain, Java-based software imagej, red, green, blue (RGB) images are automatically split in the red and green channels and a new image composed of the nonblack pixels coincident in both channels is created and inverted for better visualization. This method renders images devoid of both, extranuclear staining and background, thus emphasizing the nuclear signal. The resulting images can easily be used for comparison or quantification of the results. Given the simplicity of the technique and the worldwide diffusion of the software utilized, we think that this method could be useful in order to define standards of colocalization in confocal microscopy. +Affiliation +Department of Animal Biology, University of Málaga, Málaga, Spain. +Date-Added +2010-01-19 09:14:39 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1365-2818.2007.01719.x +Language +eng +Pii +JMI1719 +Pmid +17286699 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1365-2818.2007.01719.x + +Collins:2007p13684 +ImageJ for microscopy (article) +Author +Tony J Collins +Journal +BioTechniques +Year +2007 +Volume +43 +Number +1 Suppl +Pages +25--30 +Month +Jul +Keywords +Image Interpretation: Computer-Assisted, Microscopy, User-Computer Interface, Information Storage and Retrieval, Computer Graphics, Image Enhancement, Software, Programming Languages, Imaging: Three-Dimensional +Abstract +ImageJ is an essential tool for us that fulfills most of our routine image processing and analysis requirements. The near-comprehensive range of import filters that allow easy access to image and meta-data, a broad suite processing and analysis routine, and enthusiastic support from a friendly mailing list are invaluable for all microscopy labs and facilities-not just those on a budget. +Affiliation +Dept. Biochemistry and Biomedical Sciences, McMaster Biophotonics Facility, McMaster University, Hamilton, ON, Canada. tcollins@macbiophotonics.ca +Date-Added +2009-12-22 22:57:12 -0500 +Date-Modified +2012-06-07 09:38:05 -0400 +Language +eng +Pii +000112517 +Pmid +17936939 +Rating +0 +Url +www.biotechniques.com/article/000112517 +Local Files +~/Documents/Papers/Collins BioTechniques 2007.pdf +Remote URLs +www.biotechniques.com/article/000112517 + +Forero:2009p14918 +DeadEasy Caspase: Automatic Counting of Apoptotic Cells in Drosophila (article) +Author +Manuel G Forero and Jenny A Pennack and Anabel R Learte and Alicia Hidalgo +Journal +Plos One +Year +2009 +Volume +4 +Number +5 +Pages +e5441 +Month +Jan +Abstract +Development, cancer, neurodegenerative and demyelinating diseases, injury, and stem cell manipulations are characterised by alterations in cell number. Research into development, disease, and the effects of drugs require cell number counts. These are generally indirect estimates, because counting cells in an animal or organ is paradoxically difficult, as well as being tedious and unmanageable. Drosophila is a powerful model organism used to investigate the genetic bases of development and disease. There are Drosophila models for multiple neurodegenerative diseases, characterised by an increase in cell death. However, a fast, reliable, and accurate way to count the number of dying cells in vivo is not available. Here, we present a method based on image filtering and mathematical morphology techniques, to count automatically the number of dying cells in intact fruit-fly embryos. We call the resulting programme DeadEasy Caspase. It has been validated for Drosophila and we present examples of its power to address biological questions. Quantification is automatic, accurate, objective, and very fast. DeadEasy Caspase will be freely available as an ImageJ plug-in, and it can be modified for use in other sample types. It is of interest to the Drosophila and wider biomedical communities. DeadEasy Caspase is a powerful tool for the analysis of cell survival and cell death in development and in disease, such as neurodegenerative diseases and ageing. Combined with the power of Drosophila genetics, DeadEasy expands the tools that enable the use of Drosophila to analyse gene function, model disease and test drugs in the intact nervous system and whole animal. +Date-Added +2010-01-29 10:46:52 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1371/journal.pone.0005441 +Language +English +Pmid +000265836700013 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1371/journal.pone.0005441 + +Hecker:2008p13949 +Image analysis of time-lapse movies--a precision control guided approach to correct motion artefacts (article) +Author +David Hecker and Joachim Kappler and Alexander Glassmann and Karl Schilling and Wolfgang Alt +Journal +J Neurosci Methods +Year +2008 +Volume +172 +Number +1 +Pages +67--73 +Month +Jul +Keywords +Mice, Mice: Transgenic, Cerebellum, Mice: Inbred C57BL, Green Fluorescent Proteins, Motion, Organ Culture Techniques, Animals, PAX2 Transcription Factor, Animals: Newborn, Reference Values, Signal Processing: Computer-Assisted, Diagnostic Imaging, Artifacts +Abstract +In long-term time-lapse studies of cell migration, it is often important to distinguish active movement of individual cells from global tissue motion caused, for instance, by morphogenetic changes, or due to artefacts. We have developed a method to define and correct global movements. This is realized by the sequential morphing of image sequences to the initial image based on the position of immobile reference objects. Technically, the approach is implemented in ImageJ, using the plugin UnwarpJ. We describe an efficient way to select parameter settings such as to optimize image correction. To this end, we implemented a strict statistical control that allows to quantify image registration quality. We document this approach using a time-lapse sequence of migrating interneurons in slice cultures of the developing cerebellum. +Affiliation +Abteilung Theoretische Biologie, Institut für Zelluläre und Molekulare Botanik, University of Bonn, Germany. +Date-Added +2010-01-19 09:12:33 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jneumeth.2008.04.010 +Language +eng +Pii +S0165-0270(08)00235-5 +Pmid +18502517 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jneumeth.2008.04.010 + +Dello:2007p14800 +Liver volumetry plug and play: do it yourself with ImageJ (article) +Author +Simon A W G Dello and Ronald M van Dam and Jules J G Slangen and Marcel C G van de Poll and Marc H A Bemelmans and Jan Willem W M Greve and Regina G H Beets-Tan and Stephen J Wigmore and Cornelis H C Dejong +Journal +World J Surg +Year +2007 +Volume +31 +Number +11 +Pages +2215--21 +Month +Nov +Keywords +Retrospective Studies, Humans, Adult, Colorectal Neoplasms, Image Processing: Computer-Assisted, Liver Neoplasms, Postoperative Period, Hepatectomy, Software, Organ Size, Microcomputers, Female, Aged, Middle Aged, Liver, Tomography: X-Ray Computed +Abstract +BACKGROUND: A small remnant liver volume is an important risk factor for posthepatectomy liver failure and can be predicted accurately by computed tomography (CT) volumetry using radiologic image analysis software. Unfortunately, this software is expensive and usually requires support by a radiologist. ImageJ is a freely downloadable image analysis software package developed by the National Institute of Health (NIH) and brings liver volumetry to the surgeon's desktop. We aimed to assess the accuracy of ImageJ for hepatic CT volumetry. METHODS: ImageJ was downloaded from http://www.rsb.info.nih.gov/ij/ . Preoperative CT scans of 15 patients who underwent liver resection for colorectal cancer liver metastases were retrospectively analyzed. Scans were opened in ImageJ; and the liver, all metastases, and the intended parenchymal transection line were manually outlined on each slice. The area of each selected region, metastasis, resection specimen, and remnant liver was multiplied by the slice thickness to calculate volume. Volumes of virtual liver resection specimens measured with ImageJ were compared with specimen weights and calculated volumes obtained during pathology examination after resection. RESULTS: There was an excellent correlation between the volumes calculated with ImageJ and the actual measured weights of the resection specimens (r(2) = 0.98, p < 0.0001). The weight/volume ratio amounted to 0.88 +/- 0.04 (standard error) and was in agreement with our earlier findings using CT-linked radiologic software. CONCLUSION: ImageJ can be used for accurate hepatic CT volumetry on a personal computer. This application brings CT volumetry to the surgeon's desktop at no expense and is particularly useful in cases of tertiary referred patients, who already have a proper CT scan on CD-ROM from the referring institution. Most likely the discrepancy between volume and weight results from exsanguination of the liver after resection. +Affiliation +Department of Surgery, University Hospital, Maastricht, The Netherlands. +Date-Added +2010-01-28 21:12:08 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s00268-007-9197-x +Language +eng +Pmid +17726630 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s00268-007-9197-x + +Green:2010p15122 +Polarization Imaging and Insect Vision (article) +Author +Adam S Green and Paul R Ohmann and Nick E Leininger and James A Kavanaugh +Journal +The Physics Teacher +Year +2010 +Volume +48 +Pages +17 +Month +Jan +Keywords +physics education, laboratory techniques, light polarisation, Laboratory experiments and apparatus, Teaching methods and strategies, Image Processing, light reflection, optics, vision +Abstract +For several years we have included discussions about insect vision in the optics units of our introductory physics courses. This topic is a natural extension of demonstrations involving Brewster's reflection and Rayleigh scattering of polarized light because many insects heavily rely on optical polarization for navigation and communication. Students, especially those majoring in the life sciences, tend to find the conversation intriguing because of its interdisciplinary context. To make it even more appealing, we recently created a laboratory component that allows students to use digital cameras and polarizing filters to create polarization maps of environmental scenes and insect bodies. In this paper we describe how to do so with ImageJ, a widely used and freely available image processing program that is suitable for students with no programming experience. +Affiliation +AA(University of St. Thomas, St. Paul, MN) +Date-Added +2010-01-29 10:57:48 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1119/1.3274352 +Note +(c) 2010: American Institute of Physics +Pmid +2010PhTea..48...17G +Rating +0 +Local Files +Remote URLs +http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010PhTea..48...17G&link_type=ABSTRACT +http://dx.doi.org/10.1119/1.3274352 + +Messaoudi:2006p14003 +Multiple-axis tomography: applications to basal bodies from Paramecium tetraurelia (article) +Author +Cédric Messaoudi and Nicole Garreau de Loubresse and Thomas Boudier and Pascale Dupuis-Williams and Sergio Marco +Journal +Biol Cell +Year +2006 +Volume +98 +Number +7 +Pages +415--25 +Month +Jul +Keywords +Microtubules, Microscopy: Electron, Tomography, Cilia, Paramecium tetraurelia, Image Processing: Computer-Assisted, Algorithms, Animals +Abstract +BACKGROUND INFORMATION: Transmission electron tomography is becoming a powerful tool for studying subcellular components of cells. Classical approaches for electron tomography consist of recording images along a single-tilt axis. This approach is being improved by dual-axis reconstructions and/or high-tilt devices (tilt angle>+/-60 degrees) on microscopes to compensate part of the information loss due to the 'missing wedge' phenomena. RESULTS: In the present work we have evaluated the extension of the dual-axis technique to a multiple-axis approach, and we demonstrate a freely available plug-in for the Java-based freeware image-analysis software ImageJ. Our results from phantom and experimental data sets from Paramecium tetraurelia epon-embedded sections have shown that multiple-axis tomography achieves results equivalent to those obtained by dual-axis approach without the requirement for high-tilt devices. CONCLUSIONS: This new approach allows performance of high-resolution tomography, avoiding the need for high-tilt devices, and therefore will increase the access of electron tomography to a larger community. +Affiliation +INSERM U759, Imagerie intégrative, 91405 Orsay, France, and Institut Curie, Centre de Recherche, Laboratoire Raymond Latarjet, Centre Universitaire d'Orsay, France. +Date-Added +2010-01-19 09:16:53 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1042/BC20050097 +Language +eng +Pii +BC20050097 +Pmid +16499478 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1042/BC20050097 + +WilsonLeedy:2007p13897 +Development of a novel CASA system based on open source software for characterization of zebrafish sperm motility parameters (article) +Author +Jonas G Wilson-Leedy and Rolf L Ingermann +Journal +Theriogenology +Year +2007 +Volume +67 +Number +3 +Pages +661--72 +Month +Feb +Keywords +Reproducibility of Results, Microscopy: Video, Sperm Motility, Time Factors, Software, Male, Image Processing: Computer-Assisted, Zebrafish, Algorithms, Animals +Abstract +Although computer-assisted sperm analysis (CASA) outperforms manual techniques, many investigators rely on non-automated analysis due to the high cost of commercial options. In this study, we have written and validated a free CASA software primarily for analysis of fish sperm. This software is a plugin for the free National Institutes of Health software ImageJ and is available with documentation at . That it is open source makes possible external validation, should improve quality control and enhance the comparative value of data obtained among laboratories. In addition, we have improved upon the traditional velocity straight line (VSL) algorithm, eliminating inaccurate characterization of highly curved fish sperm paths. Using this system, the motion of zebrafish (Danio rerio) sperm was characterized relative to time post-activation and the impact of acquisition conditions upon data analysis determined. There were decreases in velocity and path straightness (STR), but not linearity (LIN), relative to time. From 30 to 300 frames/s, frame rate significantly affected curvilinear velocity (VCL) and STR measurements. Sperm density in the field of view did not affect any measured parameter. There was significant inter-male variation for VCL, VSL, velocity average path (VAP), percent motility, path character (STR, LIN), and duration of motility. Furthermore, relative sperm output (a measure reflecting both semen volume and concentration) was positively correlated to percent motility. For all motion parameters measured (except duration), the average CV was < or =10%, comparable to values obtained using commercial systems. +Affiliation +Department of Biological Sciences and Center for Reproductive Biology, University of Idaho, Moscow, ID 83844-3051, USA. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.theriogenology.2006.10.003 +Language +eng +Pii +S0093-691X(06)00550-4 +Pmid +17137620 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.theriogenology.2006.10.003 + +Gammon:2006p14011 +Spectral unmixing of multicolored bioluminescence emitted from heterogeneous biological sources (article) +Author +Seth T Gammon and W Matthew Leevy and Shimon Gross and George W Gokel and David Piwnica-Worms +Journal +Anal Chem +Year +2006 +Volume +78 +Number +5 +Pages +1520--7 +Month +Mar +Keywords +Luciferases, Hela Cells, Cell-Free System, Protein Processing: Post-Translational, Software, Transfection, Transcription: Genetic, I-kappa B Kinase, Genes: Reporter, Recombinant Fusion Proteins, Color, Diagnostic Imaging, Humans, Luminescence +Abstract +A wide variety of bioluminescent luciferase proteins are available for use in transcriptional or biochemical reporter assays. However, spectral overlap normally prevents them from being monitored simultaneously. To address this problem, a Java plug-in for ImageJ was written to deconvolute bioluminescent images composed of signals from multiple luciferases. The methodology was validated by testing the program with both simulated and real luciferase images. Bioluminescent images were acquired using a CCD camera equipped with optical filters, and the images were deconvoluted using the ImageJ plug-in. HeLa cells were transfected with either click beetle red luciferase (CBR), click beetle green luciferase (CBG99), or Renilla luciferase (Rluc), and mixed lysates were imaged in varying proportions in a 96-well plate to biochemically validate the methodology. After spectral deconvolution, the predicted, pure luciferase signals could be recovered with maximal cross-talk errors of +/-1.5%. In addition, live cells expressing CBR, CBG99, and Rluc were simultaneously imaged and deconvoluted in 96-well plates to demonstrate the feasibility of applying this methodology to high-throughput applications. Finally, multicolor transcriptional and posttranslational modification reporters were simultaneously imaged and shown to deconvolute normalized IkappaBeta kinase activity in longitudinal assays. Thus, our software provided a rapid, simple, and accurate method for simultaneously measuring multiple bioluminescent reporters in living cells. +Affiliation +Molecular Imaging Center, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA. +Date-Added +2010-01-19 09:17:44 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1021/ac051999h +Language +eng +Pmid +16503603 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1021/ac051999h + +Kam:2009p13952 +Nest expansion assay: a cancer systems biology approach to in vitro invasion measurements (article) +Author +Yoonseok Kam and Audrey Karperien and Brandy Weidow and Lourdes Estrada and Alexander R Anderson and Vito Quaranta +Journal +BMC Res Notes +Year +2009 +Volume +2 +Pages +130 +Month +Jan +Abstract +BACKGROUND: Traditional in vitro cell invasion assays focus on measuring one cell parameter at a time and are often less than ideal in terms of reproducibility and quantification. Further, many techniques are not suitable for quantifying the advancing margin of collectively migrating cells, arguably the most important area of activity during tumor invasion. We have developed and applied a highly quantitative, standardized, reproducible Nest Expansion Assay (NEA) to measure cancer cell invasion in vitro, which builds upon established wound-healing techniques. This assay involves creating uniform circular "nests" of cells within a monolayer of cells using a stabilized, silicone-tipped drill press, and quantifying the margin expansion into an overlaid extracellular matrix (ECM)-like component using computer-assisted applications. FINDINGS: The NEA was applied to two human-derived breast cell lines, MCF10A and MCF10A-CA1d, which exhibit opposite degrees of tumorigenicity and invasion in vivo. Assays were performed to incorporate various microenvironmental conditions, in order to test their influence on cell behavior and measures. Two types of computer-driven image analysis were performed using Java's freely available ImageJ software and its FracLac plugin to capture nest expansion and fractal dimension, respectively - which are both taken as indicators of invasiveness. Both analyses confirmed that the NEA is highly reproducible, and that the ECM component is key in defining invasive cell behavior. Interestingly, both analyses also detected significant differences between non-invasive and invasive cell lines, across various microenvironments, and over time. CONCLUSION: The spatial nature of the NEA makes its outcome susceptible to the global influence of many cellular parameters at once (e.g., motility, protease secretion, cell-cell adhesion). We propose the NEA as a mid-throughput technique for screening and simultaneous examination of factors contributing to cancer cell invasion, particularly suitable for parameterizing and validating Cancer Systems Biology approaches such as mathematical modeling. +Affiliation +Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA. yoonseok.kam@moffitt.org +Date-Added +2010-01-19 09:12:27 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1756-0500-2-130 +Language +eng +Pii +1756-0500-2-130 +Pmid +19594934 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1186/1756-0500-2-130 + +Irving:2007p14798 +NIH ImageJ and Slice-O-Matic computed tomography imaging software to quantify soft tissue (article) +Author +Brian A Irving and Judy Y Weltman and David W Brock and Christopher K Davis and Glenn A Gaesser and Arthur Weltman +Journal +Obesity (Silver Spring) +Year +2007 +Volume +15 +Number +2 +Pages +370--6 +Month +Feb +Keywords +Observer Variation, Humans, Adult, Image Processing: Computer-Assisted, National Institutes of Health (U.S.), Adipose Tissue, Software, Connective Tissue, Muscle: Skeletal, United States, Female, Male, Aged, Middle Aged, Body Fat Distribution, Tomography: X-Ray Computed +Abstract +OBJECTIVE: To compare reliability and limits of agreement of soft tissue cross-sectional areas obtained using Slice-O-Matic and NIH ImageJ medical imaging software packages. RESEARCH METHODS AND PROCEDURES: Abdominal and midthigh images were obtained using single-slice computed tomography. Two trained investigators analyzed each computed tomography image in duplicate. Adipose tissue and skeletal muscle cross-sectional areas (centimeters squared) were calculated using standard Hounsfield unit ranges (adipose tissue: -190 to -30 and skeletal muscle: -29 to 150). Regions of interest included abdominal total area, total fat area, subcutaneous fat area, visceral fat area (AVF), and right and left thigh total area, fat area, and skeletal muscle area. RESULTS: For all images, intra-investigator coefficients of variation ranged from 0.2% to 3.4% and from 0.4% to 5.6% and inter-investigator coefficients of variation ranged from 0.9% to 4.8% and 0.2% to 2.6% for Slice-O-Matic and NIH ImageJ, respectively, with intra- and inter-investigator coefficients of reliability of R(2) = 0.99. Mean AVF values for investigators A and B ranged from 168 to 170 cm(2) using Slice-O-Matic and NIH ImageJ. Bland-Altman analyses revealed that Slice-O-Matic and NIH ImageJ results were comparable. The mean differences (95% confidence intervals) between the AVF cross-sectional areas obtained using the Slice-O-Matic and NIH ImageJ medical imaging software were +2.5 cm(2) (-5.7, +10.8 cm(2)) or +1.4% (-3.4%, +6.4%). DISCUSSION: These findings show that both the Slice-O-Matic and NIH ImageJ medical imaging software systems provide reliable measurements of adipose tissue and skeletal muscle cross-sectional areas. +Affiliation +Department of Human Services, University of Virginia, Charlottesville, VA 22904, USA. +Date-Added +2010-01-28 21:12:08 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1038/oby.2007.573 +Language +eng +Pii +15/2/370 +Pmid +17299110 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1038/oby.2007.573 + +Ferrer:2007p14901 +An imageJ plugin to create whole body transmission scan using CT scanner: a validation study (article) +Author +L Ferrer and T Carlier and A Lisbona and M Bardies +Journal +Eur J Nucl Med Mol I +Year +2007 +Volume +34 +Pages +S198--S198 +Month +Jan +Affiliation +Ctr Rene Gauducheau, St Herblain, France +Date-Added +2010-01-29 10:43:46 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +English +Pmid +000253283900377 +Rating +0 +Local Files +Remote URLs + +Pool:2008p13891 +NeuriteTracer: a novel ImageJ plugin for automated quantification of neurite outgrowth (article) +Author +Madeline Pool and Joachim Thiemann and Amit Bar-Or and Alyson E Fournier +Journal +J Neurosci Methods +Year +2008 +Volume +168 +Number +1 +Pages +134--9 +Month +Feb +Keywords +Cells: Cultured, Ganglia: Spinal, Tubulin, Neurites, Rats: Sprague-Dawley, Enzyme Inhibitors, Pyridines, Microscopy: Fluorescence, Animals, Animals: Newborn, Neurons, Brain, Rats, Image Processing: Computer-Assisted, Cell Size, Amides, Benzimidazoles +Abstract +In vitro assays to measure neuronal growth are a fundamental tool used by many neurobiologists studying neuronal development and regeneration. The quantification of these assays requires accurate measurements of neurite length and neuronal cell numbers in neuronal cultures. Generally, these measurements are obtained through labor-intensive manual or semi-manual tracing of images. To automate these measurements, we have written NeuriteTracer, a neurite tracing plugin for the freely available image-processing program ImageJ. The plugin analyzes fluorescence microscopy images of neurites and nuclei of dissociated cultured neurons. Given user-defined thresholds, the plugin counts neuronal nuclei, and traces and measures neurite length. We find that NeuriteTracer accurately measures neurite outgrowth from cerebellar, DRG and hippocampal neurons. Values obtained by NeuriteTracer correlate strongly with those obtained by semi-manual tracing with NeuronJ and by using a sophisticated analysis package, MetaXpress. We reveal the utility of NeuriteTracer by demonstrating its ability to detect the neurite outgrowth promoting capacity of the rho kinase inhibitor Y-27632. Our plugin is an attractive alternative to existing tracing tools because it is fully automated and ready for use within a freely accessible imaging program. +Affiliation +Department of Neurology and Neurosurgery, Montreal Neurological Institute, BT-109, 3801 Rue University, Montreal, Quebec, Canada H3A 2B4. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jneumeth.2007.08.029 +Language +eng +Pii +S0165-0270(07)00430-X +Pmid +17936365 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jneumeth.2007.08.029 + +Bulut:2009p13808 +A new method of assessing the size of mandibular cysts on orthopantomograms: projection area fraction (article) +Author +Emel Bulut and Bünyamin Sahin +Journal +J Craniofac Surg +Year +2009 +Volume +20 +Number +6 +Pages +2020--3 +Month +Nov +Abstract +This study was carried out to describe a simple, accurate, and practical technique for assessing mandible cysts' area on routine orthopantomograms using digital planimetry.Forty orthopantomograms showing mandibular cysts were obtained. The digitalized images were used to measure the surface area of the half mandibles and cysts using ImageJ software by an observer. The projection area of the half mandibles and cysts was provided by the machine. The surface area fraction of the cysts within the half mandibles was estimated by using the projection area fraction (PAF) approach. Estimations were repeated on films 1 month later.The mean PAF (mean +/- SEM) obtained by the same observer in 2 sessions was 10.6% +/- 2.3% and 13.0% +/- 2.0% for the right and left sides, respectively. The estimation results of 2 sessions were compared using the Wilcoxon signed rank test. This study found no statistical difference between the estimated PAF values (P > 0.05). The estimation results of the same observer at 1-month intervals were analyzed statistically to check intraobserver variation using a correlation analysis test, which found a high degree of agreement for the results estimated using the planimetric method for the right and left sides (r = 0.994, P < 0.001 and r = 0.999, P < 0.001, respectively).The method described in this study is inexpensive and fast because planimetry can be performed within a couple of minutes per subject. This method can also be used to monitor the size difference of lesions evaluated for clinical follow-up and research. +Affiliation +Department of Oral and Maxillofacial Surgery, Ondokuz MayNs University, Kurupelit/Samsun 55139, Turkey.euzun@omu.edu.tr +Date-Added +2010-01-19 09:04:57 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1097/SCS.0b013e3181bd302e +Language +eng +Pmid +19881376 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1097/SCS.0b013e3181bd302e + +Costa:2009p13801 +Counting pollen grains using readily available, free image processing and analysis software (article) +Author +Clayton M Costa and Suann Yang +Journal +Ann Bot +Year +2009 +Volume +104 +Number +5 +Pages +1005--10 +Month +Oct +Keywords +Software, Image Processing: Computer-Assisted, Botany, Pollen, Carduus +Abstract +BACKGROUND AND AIMS: Although many methods exist for quantifying the number of pollen grains in a sample, there are few standard methods that are user-friendly, inexpensive and reliable. The present contribution describes a new method of counting pollen using readily available, free image processing and analysis software. METHODS: Pollen was collected from anthers of two species, Carduus acanthoides and C. nutans (Asteraceae), then illuminated on slides and digitally photographed through a stereomicroscope. Using ImageJ (NIH), these digital images were processed to remove noise and sharpen individual pollen grains, then analysed to obtain a reliable total count of the number of grains present in the image. A macro was developed to analyse multiple images together. To assess the accuracy and consistency of pollen counting by ImageJ analysis, counts were compared with those made by the human eye. KEY RESULTS AND CONCLUSIONS: Image analysis produced pollen counts in 60 s or less per image, considerably faster than counting with the human eye (5-68 min). In addition, counts produced with the ImageJ procedure were similar to those obtained by eye. Because count parameters are adjustable, this image analysis protocol may be used for many other plant species. Thus, the method provides a quick, inexpensive and reliable solution to counting pollen from digital images, not only reducing the chance of error but also substantially lowering labour requirements. +Affiliation +Department of Biology, 208 Mueller Laboratory, Pennsylvania State University, University Park, PA 16802, USA. +Date-Added +2010-01-19 09:06:01 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1093/aob/mcp186 +Language +eng +Pii +mcp186 +Pmid +19640891 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1093/aob/mcp186 + +Beeckman:2009p13822 +Digital titration: automated image acquisition and analysis of load and growth of Chlamydophila psittaci (article) +Author +Delphine S A Beeckman and Geert Meesen and Patrick Van Oostveldt and Daisy Vanrompay +Journal +Microsc. Res. Tech. +Year +2009 +Volume +72 +Number +5 +Pages +398--402 +Month +May +Keywords +Cell Line, Bacteriological Techniques, Chickens, Chlamydophila psittaci, Image Processing: Computer-Assisted, Microscopy, Microbial Viability, Animals +Abstract +Traditionally, the amount of infective chlamydiae in a given sample is determined by inoculating dilution series into cell cultures and physically counting chlamydial inclusions. This approach is time consuming, tedious, and error prone, mainly when dealing with high titers. Therefore, this paper describes a largely automated technique that was developed to standardize the determination of chlamydial load in vitro. Cells are fixed at 36 h post-inoculation and bacteria visualized using standard immunological detection methods. Consequently, for 81 microscopic fields, an image is recorded at the interpolated focal plane. These images are then automatically processed using an ImageJ plugin and the obtained results are imported into Excel to determine the number of inclusion forming units per mL in the sample. The main advantage of this technique is that no or minimal sample dilution is required, thus minimizing dilution errors. In addition, this technique was employed during the early, middle and late growth stages of the chlamydial developmental cycle and results correlated well (P < 0.01) with 16S rRNA values from previous experiments, thereby proving its suitability to follow chlamydial growth in vitro. The method described is highly suitable for high throughput titration of cell culture inoculated samples and assessment of possible antichlamydial effects of novel compounds throughout the chlamydial growth cycle. +Affiliation +Faculty of Bioscience Engineering, Department of Molecular Biotechnology (BW14), Ghent University, Coupure Links 653, Gent, Belgium. delphine.beeckman@ugent.be +Date-Added +2010-01-19 09:09:15 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/jemt.20694 +Language +eng +Pmid +19165738 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/jemt.20694 + +Karmonik:2010p13794 +An image analysis pipeline for the semi-automated analysis of clinical fMRI images based on freely available software (article) +Author +Christof Karmonik and Michele York and Robert Grossman and Ekta Kakkar and Krutina Patel and Hani Haykal and David King +Journal +Computers in biology and medicine +Year +2010 +Month +Jan +Abstract +The technique of functional Magnetic Resonance Imaging (fMRI) has evolved in the last 15 years from a research concept into a clinically relevant medical procedure. In this study, an efficient, semi-automated and cost-effective solution for the analysis of fMRI images acquired in a clinical setting is presented relying heavily on open source software. The core of the pipeline is the software Analysis of Functional NeuroImages (AFNI, National Institute of Mental Health (NIMH)) combined with K-PACS and ImageJ. Its application is illustrated with clinical fMRI exams and with a research study involving comparing subjects diagnosed with Parkinson's disease and age-matched controls. +Affiliation +Department of Neurosurgery, The Methodist Hospital, Houston, TX, USA. +Date-Added +2010-01-19 08:59:39 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.compbiomed.2009.12.003 +Language +ENG +Pii +S0010-4825(09)00219-4 +Pmid +20074720 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.compbiomed.2009.12.003 + +Thevenaz:2007p15226 +User-friendly semiautomated assembly of accurate image mosaics in microscopy (article) +Author +Philippe Thévenaz and Michael Unser +Journal +Microsc. Res. Tech. +Year +2007 +Volume +70 +Number +2 +Pages +135--46 +Month +Feb +Keywords +Algorithms, Microscopy, Image Processing: Computer-Assisted, Software +Abstract +We present a semiautomated software solution to the problem of extending the lateral field of view of a classical microscope. The initial requirements are a set of overlapping images, along with their user-provided coarse mosaic. Our solution then refines this initial mosaic in a fully automatic fashion. We rely on a highly accurate registration engine to perform the pairwise registration of the individual images, and on an efficient strategy to minimize the amount of computations while maintaining the highest possible global quality. We describe these ingredients, which we make available as a free multiplatform user-friendly software package. We also highlight why and how the specific aspects of the present microscopy application differ from those encountered while creating more common mosaics such as panoramas. Finally, we present experimental results that illustrate and validate our method on a real biological sample. We conclude by showing that we are able to reach subpixel accuracy. +Affiliation +Ecole polytechnique fédérale de Lausanne, Biomedical Imaging Group, Lausanne VD, Switzerland. philippe.thevenaz@epfl.ch +Date-Added +2010-01-29 11:07:59 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/jemt.20393 +Language +eng +Pmid +17133410 +Rating +0 +Local Files +Remote URLs +http://www3.interscience.wiley.com/journal/113490179/abstract?CRETRY=1&SRETRY=0 +http://dx.doi.org/10.1002/jemt.20393 + +Kobayashi:2009p13802 +Technical note: a tool for determining rotational tilt axis with or without fiducial markers (article) +Author +Atsuko Kobayashi and Takumi Fujigaya and Masayuki Itoh and Takahisa Taguchi and Hiroshi Takano +Journal +Ultramicroscopy +Year +2009 +Volume +110 +Number +1 +Pages +1--6 +Month +Dec +Abstract +Virtually all reliable TEM tomographic reconstructions in life science depend upon cross-correlating successive images in a tilt-stack, and then using gold nanobeads as fiducial markers for determining the relative image rotation axis. Although the rotational tilt angle is one of the essential parameters affecting the quality of tomographic reconstructions, little is discussed about its determination. We provide here a simple tool based on the property of Fast Fourier Transformation for determining this rotation axis offset angle. Our method uses two publicly-available software packages (IMOD and ImageJ), and can be used on any TEM-based image stack, which is useful for images with poor bead distribution or situations where such beads are not visible. We illustrate this procedure with two different biological samples, one of which is a plunge frozen cryo-sample with fiducials and the other an epon-embedded thin section without fiducials. Prior knowledge of the rotational tilt angle facilitates further processing tomograms. With cross-correlation and the FFT-obtained rotational tilt angle, we reconstructed tomograms, of which the cross-section did not show "arc" distortion. This tool could be easily incorporated into any software for the alignment with or without fiducials. +Affiliation +Photonics Research Institute, National Institute of Advanced Industrial Science and Technology, Midorigaoka 1-8-31, Ikeda-city, Osaka 563-8577, Japan. kobayashi-a@aist.go.jp +Date-Added +2010-01-19 09:01:15 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.ultramic.2009.08.007 +Language +eng +Pii +S0304-3991(09)00194-6 +Pmid +19781856 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.ultramic.2009.08.007 + +Macdonald:2009p13890 +Anterior-posterior bending strength at the tibial shaft increases with physical activity in boys: evidence for non-uniform geometric adaptation (article) +Author +H M Macdonald and D M L Cooper and H A McKay +Journal +Osteoporos Int +Year +2009 +Volume +20 +Number +1 +Pages +61--70 +Month +Jan +Keywords +Humans, Adaptation: Physiological, Pliability, Child, Male, Absorptiometry: Photon, Biomechanics, Bone Development, Tibia, Tomography: X-Ray Computed, Time Factors, Bone Density, Motor Activity, Linear Models +Abstract +We investigated bone structural adaptations to a 16-month school-based physical activity intervention in 202 young boys using a novel analytical method for peripheral quantitative computed tomography scans of the tibial mid-shaft. Our intervention effectively increased bone bending strength in the anterior-posterior plane as estimated with the maximum second moment of area (I(max)). INTRODUCTION: We previously reported positive effects of a physical activity intervention on peripheral quantitative computed tomography (pQCT)-derived bone strength at the tibial mid-shaft in young boys. The present study further explored structural adaptations to the intervention using a novel method for pQCT analysis. METHODS: Participants were 202 boys (aged 9-11 years) from 10 schools randomly assigned to control (CON, 63 boys) and intervention (INT, 139 boys) groups. INT boys participated in 60 min/week of classroom physical activity, including a bone-loading program. We used ImageJ to process pQCT images of the tibial mid-shaft and determine the second moments of area (I(max), I(min)) and cortical area (CoA) and thickness (CTh) by quadrant (anterior, medial, lateral, posterior). We defined quadrants according to pixel coordinates about the centroid. We used mixed linear models to compare change in bone outcomes between groups. RESULTS: The INT boys had a 3% greater gain in I(max) than the CON boys (p = 0.04) and tended to have a greater gain in I(min) ( approximately 2%, NS). Associated with the greater gain in I(max) was a slightly greater (NS) gain (1-1.4%) in CoA and CTh in the anterior, medial, and posterior (but not lateral) quadrants. CONCLUSION: Our results suggest regional variation in bone adaptation consistent with patterns of bone formation induced by anterior-posterior bending loads. +Affiliation +Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB, Canada. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s00198-008-0636-9 +Language +eng +Pmid +18496638 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s00198-008-0636-9 + +Feige:2005p14802 +PixFRET, an ImageJ plug-in for FRET calculation that can accommodate variations in spectral bleed-throughs (article) +Author +Jérôme N Feige and Daniel Sage and Walter Wahli and Béatrice Desvergne and Laurent Gelman +Journal +Microsc. Res. Tech. +Year +2005 +Volume +68 +Number +1 +Pages +51--8 +Month +Sep +Keywords +Fluorescent Dyes, Receptors: Cytoplasmic and Nuclear, Staining and Labeling, Fluorescence Resonance Energy Transfer, Microscopy: Fluorescence, Image Processing: Computer-Assisted +Abstract +Fluorescence resonance energy transfer (FRET) allows the user to investigate interactions between fluorescent partners. One crucial issue when calculating sensitized emission FRET is the correction for spectral bleed-throughs (SBTs), which requires to calculate the ratios between the intensities in the FRET and in the donor or acceptor settings, when only the donor or acceptor are present. Theoretically, SBT ratios should be constant. However, experimentally, these ratios can vary as a function of fluorophore intensity, and assuming constant values may hinder precise FRET calculation. One possible cause for such a variation is the use of a microscope set-up with different photomultipliers for the donor and FRET channels, a set-up allowing higher speed acquisitions on very dynamic fluorescent molecules in living cells. Herein, we show that the bias introduced by the differential response of the two PMTs can be circumvented by a simple modeling of the SBT ratios as a function of fluorophore intensity. Another important issue when performing FRET is the localization of FRET within the cell or a population of cells. We hence developed a freely available ImageJ plug-in, called PixFRET, that allows a simple and rapid determination of SBT parameters and the display of normalized FRET images. The usefulness of this modeling and of the plug-in are exemplified by the study of FRET in a system where two interacting nuclear receptors labeled with ECFP and EYFP are coexpressed in living cells. +Affiliation +Center for Integrative Genomics, NCCR Frontiers in Genetics, University of Lausanne, Switzerland. +Date-Added +2010-01-28 21:12:09 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/jemt.20215 +Language +eng +Pmid +16208719 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/jemt.20215 + +Iannuccelli:2010p13791 +NEMO: a tool for analyzing gene and chromosome territory distributions from 3D-FISH experiments (article) +Author +E Iannuccelli and F Mompart and J Gellin and Y Lahbib-Mansais and M Yerle and T Boudier +Journal +Bioinformatics +Year +2010 +Volume +26 +Number +5 +Pages +696--7 +Month +Jan +Abstract +SUMMARY: Three-dimensional fluorescence in situ hybridization (3D-FISH) is used to study the organization and the positioning of chromosomes or specific sequences such as genes or RNA in cell nuclei. Many different programs (commercial or free) allow image analysis for 3D-FISH experiments. One of the more efficient open-source programs for automatically processing 3D-FISH microscopy images is Smart 3D-FISH, an ImageJ plug-in designed to automatically analyze distances between genes. One of the drawbacks of Smart 3D-FISH is that it has a rather basic user interface and produces its results in various text and image files thus making the data post-processing step time-consuming. We developed a new Smart 3D-FISH graphical user interface, NEMO, which provides all information in the same place so that results can be checked and validated efficiently. NEMO give users the ability to drive their experiments analysis in either automatic, semi-automatic or manual detection mode. We also tuned Smart 3D-FISH to better analyze chromosome territories. AVAILABILITY: NEMO is a standalone Java application available for Windows and Linux platforms. The program is distributed under the creative commons licence and can be freely downloaded from https://www-lgc.toulouse.inra.fr/internet/index.php/Tools/Nemo.html CONTACT: eddie.iannuccelli@toulouse.inra.fr. +Affiliation +INRA, Laboratoire de Génétique Cellulaire, BP 52627, 31326 Castanet-Tolosan. +Date-Added +2010-01-19 08:59:35 -0500 +Date-Modified +2012-06-06 23:05:06 -0400 +Doi +10.1093/bioinformatics/btq013 +Language +ENG +Pii +btq013 +Pmid +20080510 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1093/bioinformatics/btq013 + +Kilimnik:2009p13790 +Quantification of pancreatic islet distribution in situ in mice (article) +Author +German Kilimnik and Abraham Kim and Junghyo Jo and Kevin Miller and Manami Hara +Journal +Am J Physiol Endocrinol Metab +Year +2009 +Volume +297 +Number +6 +Pages +E1331--8 +Month +Dec +Keywords +Promoter Regions: Genetic, Immunohistochemistry, Green Fluorescent Proteins, Insulin, Image Processing: Computer-Assisted, Mice, Animals, Insulin-Secreting Cells, Mice: Transgenic +Abstract +Tracing changes of specific cell populations in health and disease is an important goal of biomedical research. Precisely monitoring pancreatic beta-cell proliferation and islet growth is a challenging area of research. We have developed a method to capture the distribution of beta-cells in the intact pancreas of transgenic mice with fluorescence-tagged beta-cells with a macro written for ImageJ (rsb.info.nih.gov/ij/). Total beta-cell area and islet number and size distribution are quantified with reference to specific parameters and location for each islet and for small clusters of beta-cells. The entire distribution of islets can now be plotted in three dimensions, and the information from the distribution on the size and shape of each islet allows a quantitative and a qualitative comparison of changes in overall beta-cell area at a glance. +Affiliation +Department of Medicine, The University of Chicago, Chicago, Illinois 60637, USA. +Date-Added +2010-01-19 09:03:14 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1152/ajpendo.00479.2009 +Language +eng +Pii +ajpendo.00479.2009 +Pmid +19808908 +Rating +0 +Local Files +Remote URLs +http://ajpendo.physiology.org/cgi/content/full/297/6/E1331 +http://dx.doi.org/10.1152/ajpendo.00479.2009 + +Igathinathane:2008p14900 +Shape identification and particles size distribution from basic shape parameters using ImageJ (article) +Author +C Igathinathane and LO Pordesimo and EP Columbus and WD Batchelor and SR Methuku +Journal +Comput Electron Agr +Year +2008 +Volume +63 +Number +2 +Pages +168--182 +Month +Jan +Keywords +Imagej, Image Processing, Shape Identification, Physical Properties, Plugin, Machine Vision +Abstract +Quick and accurate particle size distribution analysis is desirable in various technical fields that handle granular or particulate materials including size reduction. We developed an ImageJ plugin that extracts the dimensions from a digital image of disjoint particles after identifying their shapes and determines their particles size distribution. We established that the major and minor axes of ImageJ fitted ellipse along with the developed correction factors efficiently determined dimensions of particles. This paper describes the plugin development and its application to food grains and ground biomass. Using computer generated geometrical shapes as reference objects, a shape identification strategy that addresses common geometric shapes such as square, inclined square, rectangle, inclined rectangle, circle, ellipse, and inclined ellipse was developed. The strategy used only three newly defined shape parameters to identify objects, such as reciprocal aspect ratio, rectangularity, and feret major axis ratio from the standard outputs generated by ImageJ. Evaluation of effects of the particles shape, size, and orientation on the deviation from the reference particle's length and width indicated that the mean absolute deviations of all these factors were less than 1.3%. Developed plugin was applied successfully to analyze the dimensions and size distribution of food grains and ground Miscanthus particles images. The plugin produced quick and accurate size distribution of particles from digital images and can be applied to variety of particle analysis applications.. (C) 2008 Elsevier B.V. All rights reserved. +Affiliation +Mississippi State Univ, Dept Agr {\&} Biol Engn, Mississippi State, MS 39762 USA +Date-Added +2010-01-29 10:43:45 -0500 +Date-Modified +2011-07-06 15:22:18 -0400 +Doi +10.1016/j.compag.2008.02.007 +Language +English +Pmid +000258367600009 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.compag.2008.02.007 + +Abramoff:2004p4386 +Image Processing with ImageJ (article) +Author +MD Abramoff and PJ Magalhaes and S J Ram +Journal +{Biophotonics International \textup{(available at \url{http://webeye.ophth.uiowa.edu/dept/biograph/abramoff/imagej.pdf})}} +Year +2004 +Volume +11 +Number +7 +Pages +36--42 +Abstract +ImageJ official reference +Date-Added +2008-11-19 06:28:01 -0500 +Date-Modified +2011-07-06 15:24:31 -0400 +Label +rec-number 5 +Rating +0 +Local Files +Remote URLs + +Roszik:2008p13950 +AccPbFRET: an ImageJ plugin for semi-automatic, fully corrected analysis of acceptor photobleaching FRET images (article) +Author +János Roszik and János Szöllosi and György Vereb +Journal +BMC Bioinformatics +Year +2008 +Volume +9 +Pages +346 +Month +Jan +Keywords +Programming Languages, Artifacts, Artificial Intelligence, Protein Interaction Mapping, Software, Pattern Recognition: Automated, Fluorescence Recovery After Photobleaching, Sensitivity and Specificity, Reproducibility of Results, Algorithms +Abstract +BACKGROUND: The acceptor photobleaching fluorescence resonance energy transfer (FRET) method is widely used for monitoring molecular interactions in cells. This method of FRET, while among those with the simplest mathematics, is robust, self-controlled and independent of fluorophore amounts and ratios. RESULTS: AccPbFRET is a user-friendly, efficient ImageJ plugin which allows fully corrected, pixel-wise calculation and detailed, ROI (region of interest)-based analysis of FRET efficiencies in microscopic images. Furthermore, automatic registration and semi-automatic analysis of large image sets is provided, which are not available in any existing FRET evaluation software. CONCLUSION: Despite of the widespread applicability of the acceptor photobleaching FRET technique, this is the first paper where all possible sources of major errors of the measurement and analysis are considered, and AccPbFRET is the only program which provides the complete suite of corrections--for registering image pairs, for unwanted photobleaching of the donor, for cross-talk of the acceptor and/or its photoproduct to the donor channel and for partial photobleaching of the acceptor. The program efficiently speeds up the analysis of large image sets even for novice users and is freely available. +Affiliation +Department of Biophysics and Cell Biology, Research Center for Molecular Medicine, University of Debrecen, Debrecen, Hungary. janosr@dote.hu +Date-Added +2010-01-19 09:12:37 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1471-2105-9-346 +Language +eng +Pii +1471-2105-9-346 +Pmid +18713453 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1186/1471-2105-9-346 + +Grochowsky:2006p14002 +Digital photogrammetry for quantitative wear analysis of retrieved TKA components (article) +Author +J C Grochowsky and L W Alaways and R Siskey and E Most and S M Kurtz +Journal +J Biomed Mater Res Part B Appl Biomater +Year +2006 +Volume +79 +Number +2 +Pages +263--7 +Month +Nov +Keywords +Biocompatible Materials, Materials Testing, Humans, Polyethylenes, Knee Prosthesis, Photogrammetry +Abstract +The use of new materials in knee arthroplasty demands a way in which to accurately quantify wear in retrieved components. Methods such as damage scoring, coordinate measurement, and in vivo wear analysis have been used in the past. The limitations in these methods illustrate a need for a different methodology that can accurately quantify wear, which is relatively easy to perform and uses a minimal amount of expensive equipment. Off-the-shelf digital photogrammetry represents a potentially quick and easy alternative to what is readily available. Eighty tibial inserts were visually examined for front and backside wear and digitally photographed in the presence of two calibrated reference fields. All images were segmented (via manual and automated algorithms) using Adobe Photoshop and National Institute of Health ImageJ. Finally, wear was determined using ImageJ and Rhinoceros software. The absolute accuracy of the method and repeatability/reproducibility by different observers were measured in order to determine the uncertainty of wear measurements. To determine if variation in wear measurements was due to implant design, 35 implants of the three most prevalent designs were subjected to retrieval analysis. The overall accuracy of area measurements was 97.8%. The error in automated segmentation was found to be significantly lower than that of manual segmentation. The photogrammetry method was found to be reasonably accurate and repeatable in measuring 2-D areas and applicable to determining wear. There was no significant variation in uncertainty detected among different implant designs. Photogrammetry has a broad range of applicability since it is size- and design-independent. A minimal amount of off-the-shelf equipment is needed for the procedure and no proprietary knowledge of the implant is needed. +Affiliation +Implant Research Center, School of Biomedical Engineering, Drexel University, Philadelphia, PA 19104, USA. jared.chase.grochowsky@drexel.edu +Date-Added +2010-01-19 09:14:28 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/jbm.b.30537 +Language +eng +Pmid +16649169 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/jbm.b.30537 + +Grewal:2008p13892 +Pentacam tomograms: a novel method for quantification of posterior capsule opacification (article) +Author +Dilraj Grewal and Rajeev Jain and Gagandeep Singh Brar and Satinder Pal Singh Grewal +Journal +Invest Ophthalmol Vis Sci +Year +2008 +Volume +49 +Number +5 +Pages +2004--8 +Month +May +Keywords +Tomography, Photography, Middle Aged, Diagnostic Techniques: Ophthalmological, Aged: 80 and over, Lens Capsule: Crystalline, Image Processing: Computer-Assisted, Aged, Cataract, Reproducibility of Results, Humans, Adult +Abstract +PURPOSE: To develop and validate a method to quantify posterior capsule opacification (PCO) in eyes after cataract surgery and intraocular lens implantation using Scheimpflug Pentacam tomograms and compare its validity with slit lamp retroillumination image analysis. METHODS: One hundred twenty-four pseudophakic eyes of 124 patients were divided into two groups. Group 1 consisted of 40 eyes with visually significant PCO, and group 2 consisted of 84 eyes without visually significant PCO. Pentacam Imaging was performed after full mydriasis using the 50-scan acquisition protocol, and high-resolution tomograms were reconstructed and analyzed using ImageJ freeware. Retroillumination photographs were captured for group 1 eyes using the Topcon digital slit lamp, and these were analyzed using POCOman software to calculate an aggregate severity grade and percentage PCO value. Correlation coefficients were calculated for PCO values obtained using POCOman and ImageJ. RESULTS: Mean PCO percentage value obtained using POCOman software was 23.34 +/- 6.25 U, mean aggregate PCO severity grade was 0.46 +/- 0.28 U, and mean pixel-intensity value using ImageJ was 31.071 +/- 8.26 U. There was a significant positive correlation between the percentage PCO (P = 0.000; r = 0.864) and PCO severity grade (P = 0.001; r = 0.490) obtained for group 1 eyes using slit lamp retroillumination images and PCO pixel intensity obtained using Pentacam tomograms. CONCLUSIONS: Retroillumination photographs are the standard for quantifying PCO. Pentacam tomograms are easier to obtain and are free of flash reflections, and they allow for a more objective analysis. The correlation between the two methods demonstrates that ImageJ analysis of Pentacam tomograms is a viable tool for PCO analysis. +Affiliation +Grewal Eye Institute, Chandigarh, India. dilraj@gmail.com +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1167/iovs.07-1056 +Language +eng +Pii +49/5/2004 +Pmid +18436833 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1167/iovs.07-1056 + +Gering:2004p14013 +A rapid method for counting nucleated erythrocytes on stained blood smears by digital image analysis (article) +Author +Eben Gering and Carter T Atkinson +Journal +J Parasitol +Year +2004 +Volume +90 +Number +4 +Pages +879--81 +Month +Aug +Keywords +Malaria: Avian, Time Factors, Parasitemia, Erythrocytes, Birds, Image Processing: Computer-Assisted, Animals, Erythrocyte Count +Abstract +Measures of parasitemia by intraerythrocytic hematozoan parasites are normally expressed as the number of infected erythrocytes per n erythrocytes and are notoriously tedious and time consuming to measure. We describe a protocol for generating rapid counts of nucleated erythrocytes from digital micrographs of thin blood smears that can be used to estimate intensity of hematozoan infections in nonmammalian vertebrate hosts. This method takes advantage of the bold contrast and relatively uniform size and morphology of erythrocyte nuclei on Giemsa-stained blood smears and uses ImageJ, a java-based image analysis program developed at the U.S. National Institutes of Health and available on the internet, to recognize and count these nuclei. This technique makes feasible rapid and accurate counts of total erythrocytes in large numbers of microscope fields, which can be used in the calculation of peripheral parasitemias in low-intensity infections. +Affiliation +Molecular Genetics Laboratory, National Museum of Natural History, Smithsonian Institution, 3001 Connecticut Avenue, NW, Washington, DC 20008-0551, USA. +Date-Added +2010-01-19 09:18:35 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +eng +Pmid +15357090 +Rating +0 +Local Files +Remote URLs + +Myrick:2009p14960 +A low-cost system for capturing and analyzing the motion of aquatic organisms (article) +Author +Christopher A Myrick +Journal +J N Am Benthol Soc +Year +2009 +Volume +28 +Number +1 +Pages +101--109 +Month +Jan +Keywords +Preference, Behavior, Performance, Chinook Salmon, Video Capture, Securityspy Software, Firewire Camera, Motion Analysis, Nih Imagej, New Zealand Mudsnails +Abstract +Capture and quantitative analysis of the motion of organisms is a powerful tool that can be used in diverse biological. fields including physiology, behavior, kinematics, and ecology. A number of high-end commercial motion capture and analysis systems that offer a wide array of features and image capture and analysis capabilities are available. However, few, if any, such systems are low cost and could be used for projects with small budgets or by researchers interested in collecting pilot data before upgrading to an expensive motion capture and analysis system. Our paper describes a low-cost (<{\$}US1000, not including the cost of the computer) motion capture and analysis system that simultaneously captures live video from 5 digital video cameras (Unibrain Fire-i FireWire [IEEE 1394]) using standard security camera software (SecuritySpy 1.3.1). The video analyses are carried out using a combination of standard spreadsheet software (Microsoft Excel) and a freeware image-analysis program (NIH Image J), with one of the available particle-tracking plugins. Tests using New Zealand mudsnails (Potamopyrgus antipodarum) demonstrated that the system could record and accurately track the movement of small (4 mm) targets. Recommendations for designing similar project-specific systems are provided. +Affiliation +Colorado State Univ, Dept Fish Wildlife {\&} Conservat Biol, Ft Collins, CO 80523 USA +Date-Added +2010-01-29 10:45:44 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1899/08-067.1 +Language +English +Pmid +000263481300010 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1899/08-067.1 + +Jabbour:2009p13998 +A new approach to geometrical measurements in an animal model of vocal fold scar (article) +Author +Noel Jabbour and Priya D Krishna and James Osborne and Clark A Rosen +Journal +J Voice +Year +2009 +Volume +23 +Number +1 +Pages +88--94 +Month +Jan +Keywords +Laryngeal Mucosa, Vocal Cords, Image Processing: Computer-Assisted, Reproducibility of Results, Dogs, Animals, Laryngeal Diseases +Abstract +A standard method for quantifying the geometric properties of vocal folds has not been widely adopted. An ideal method of geometrical measurement should effectively quantify the dimensions of the medial vibratory portion of the vocal fold, should be easily performed, should yield consistent results, and should be readily available at little to no cost. We have developed a new approach for geometrical measurements to meet these goals. The objective of this study is to describe this new approach and to assess its effectiveness in a canine model of vocal fold scar. One hundred thirty-five mid-membranous coronal sections of vocal folds from 10 canines (five with unilateral surgical scarring) were examined by light microscopy; digital images were captured. ImageJ was used to measure a variety of described parameters. Comparison between scarred vocal folds and control vocal folds was made. At least 20% of the slides for each vocal fold were randomly selected (n=42) for repeat measurements of interrater and intrarater reliability. A statistically significant difference between scarred and control vocal folds was obtained for horizontal distance (P<0.001), vertical distance (P=0.005), area (P<0.001), mean optical density (OD) (P<0.001), and OD at defined points along the length of the vocal fold (P< or =0.009). Reliability calculations for intrarater and interrater measurements ranged from r=0.845 to r=0.994 and from r=0.734 to r=0.976, respectively. The proposed approach for geometrical measurements meets the intended objectives in a canine model of vocal fold scar. Future work is needed to apply this approach to other model systems. +Affiliation +University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA. +Date-Added +2010-01-19 09:16:20 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jvoice.2007.07.002 +Language +eng +Pii +S0892-1997(07)00089-6 +Pmid +17981013 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jvoice.2007.07.002 + +Roszik:2009p13818 +Evaluation of intensity-based ratiometric FRET in image cytometry--approaches and a software solution (article) +Author +János Roszik and Duarte Lisboa and János Szöllosi and György Vereb +Journal +Cytometry A +Year +2009 +Volume +75 +Number +9 +Pages +761--7 +Month +Sep +Keywords +Image Cytometry, Software, Pattern Recognition: Automated, Fluorescence Recovery After Photobleaching, Cell Line: Tumor, Fluorescence Resonance Energy Transfer, Microscopy: Confocal, Humans +Abstract +The intensity-based ratiometric FRET (fluorescence resonance energy transfer) method is a powerful technique for following molecular interactions in living cells. Since it is not based on irreversibly destroying the donor or the acceptor fluorophores, the time course of changes in FRET efficiency values can be monitored by this method. ImageJ, a sophisticated software tool for many types of image processing allows users to extend it with programs for various purposes. Implementing intensity-based ratiometric FRET with ImageJ vastly enhances the applicability of the FRET method. We developed an efficient ImageJ plugin, RiFRET, which calculates FRET efficiency on a pixel-by-pixel basis from ratiometric FRET images. It allows the user to correct for channel cross-talk (bleed-through) and to calculate FRET from image stacks, i.e., from 3D data sets. Semiautomatic processing for larger datasets is also included in the program. Furthermore, several options for calibrating FRET efficiency calculations were tested and their applicability to various expression systems is discussed. Although the ratiometric FRET method is widely applied, our plugin is the first freely available software for evaluating such FRET data. The program is user friendly and provides reliable, standardized results. +Affiliation +Department of Biophysics and Cell Biology, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary. +Date-Added +2010-01-19 09:06:56 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/cyto.a.20747 +Language +eng +Pmid +19591240 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/cyto.a.20747 + +McAtee:2009p13997 +A rapid method of fruit cell isolation for cell size and shape measurements (article) +Author +Peter A McAtee and Ian C Hallett and Jason W Johnston and Robert J Schaffer +Journal +Plant Methods +Year +2009 +Volume +5 +Pages +5 +Month +Jan +Abstract +ABSTRACT: BACKGROUND: Cell size is a structural component of fleshy fruit, contributing to important traits such as fruit size and texture. There are currently a number of methods for measuring cell size; most rely either on tissue sectioning or digestion of the tissue with cell wall degrading enzymes or chemicals to release single cells. Neither of these approaches is ideal for assaying large fruit numbers as both require a considerable time to prepare the tissue, with current methods of cell wall digestions taking 24 to 48 hours. Additionally, sectioning can lead to a measurement of a plane that does not represent the widest point of the cell. RESULTS: To develop a more rapid way of measuring fruit cell size we have developed a protocol that solubilises pectin in the middle lamella of the plant cell wall releasing single cells into a buffered solution. Gently boiling small fruit samples in a 0.05 M Na2CO3 solution, osmotically balanced with 0.3 M mannitol, produced good cell separation with little cellular damage in less than 30 minutes. The advantage of combining a chemical treatment with boiling is that the cells are rapidly killed. This stopped cell shape changes that could potentially occur during separation. With this method both the rounded and angular cells of the apple cultivars SciRos 'Pacific Rose' and SciFresh 'Jazz' were observed in the separated cells. Using this technique, an in-depth analysis was performed measuring cell size from 5 different apple cultivars. Cell size was measured using the public domain ImageJ software. For each cultivar a minimum of 1000 cells were measured and it was found that each cultivar displayed a different distribution of cell size. Cell size within cultivars was similar and there was no correlation between flesh firmness and cell size. This protocol was tested on tissue from other fleshy fruit including tomato, rock melon and kiwifruit. It was found that good cell separation was achieved with flesh tissue from all these fruit types, showing a broad utility to this protocol. CONCLUSION: We have developed a method for isolating single cells from fleshy fruit that reduces the time needed for fruit cell separation. This method was used to demonstrate differences in cell size and shape for 5 different apple cultivars. While firmness between the different cultivars is independent of cell size, apples with more angular cells appear to be firmer. +Affiliation +The New Zealand Institute for Plant {\&} Food Research, Private Bag 92169, Auckland 1142, New Zealand. rschaffer@hortresearch.co.nz. +Date-Added +2010-01-19 09:15:42 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1746-4811-5-5 +Language +eng +Pii +1746-4811-5-5 +Pmid +19402911 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1186/1746-4811-5-5 + +Noursadeghi:2008p13903 +Quantitative imaging assay for NF-$\kappa$B nuclear translocation in primary human macrophages (article) +Author +Mahdad Noursadeghi and Jhen Tsang and Thomas Haustein and Robert F Miller and Benjamin M Chain and David R Katz +Journal +J Immunol Methods +Year +2008 +Volume +329 +Number +1-2 +Pages +194--200 +Month +Jan +Keywords +Time Factors, Cell Line, Macrophages, Cell Culture Techniques, Polymyxin B, Transfection, Cell Nucleus, Signal Processing: Computer-Assisted, Microscopy: Confocal, Cells: Cultured, Peptides, Toll-Like Receptor 2, Transcription Factor RelA, Active Transport: Cell Nucleus, Genes: Reporter, Macrophage Activation, Microscopy: Fluorescence, Humans, Lipopeptides, Lipopolysaccharides, Software, Spectrophotometry, Dose-Response Relationship: Drug, Reproducibility of Results +Abstract +Quantitative measurement of NF-kappaB nuclear translocation is an important research tool in cellular immunology. Established methodologies have a number of limitations, such as poor sensitivity, high cost or dependence on cell lines. Novel imaging methods to measure nuclear translocation of transcriptionally active components of NF-kappaB are being used but are also partly limited by the need for specialist imaging equipment or image analysis software. Herein we present a method for quantitative detection of NF-kappaB rel A nuclear translocation, using immunofluorescence microscopy and the public domain image analysis software ImageJ that can be easily adopted for cellular immunology research without the need for specialist image analysis expertise and at low cost. The method presented here is validated by demonstrating the time course and dose response of NF-kappaB nuclear translocation in primary human macrophages stimulated with LPS, and by comparison with a commercial NF-kappaB activation reporter cell line. +Affiliation +Department of Immunology {\&} Molecular Pathology, University College London, Windeyer Building, 46 Cleveland Street, W1T 4JF London, UK. m.noursadeghi@ucl.ac.uk +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jim.2007.10.015 +Language +eng +Pii +S0022-1759(07)00340-7 +Pmid +18036607 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jim.2007.10.015 + +Sage:2005p14001 +Automatic tracking of individual fluorescence particles: application to the study of chromosome dynamics (article) +Author +Daniel Sage and Franck R Neumann and Florence Hediger and Susan M Gasser and Michael Unser +Journal +IEEE Trans Image Process +Year +2005 +Volume +14 +Number +9 +Pages +1372--83 +Month +Sep +Keywords +Microscopy: Video, Chromosomes, Image Enhancement, Image Interpretation: Computer-Assisted, Artificial Intelligence, Sensitivity and Specificity, Motion, Microscopy: Fluorescence, Algorithms, Pattern Recognition: Automated, Subtraction Technique, Reproducibility of Results +Abstract +We present a new, robust, computational procedure for tracking fluorescent markers in time-lapse microscopy. The algorithm is optimized for finding the time-trajectory of single particles in very noisy dynamic (two- or three-dimensional) image sequences. It proceeds in three steps. First, the images are aligned to compensate for the movement of the biological structure under investigation. Second, the particle's signature is enhanced by applying a Mexican hat filter, which we show to be the optimal detector of a Gaussian-like spot in 1/omega2 noise. Finally, the optimal trajectory of the particle is extracted by applying a dynamic programming optimization procedure. We have used this software, which is implemented as a Java plug-in for the public-domain ImageJ software, to track the movement of chromosomal loci within nuclei of budding yeast cells. Besides reducing trajectory analysis time by several 100-fold, we achieve high reproducibility and accuracy of tracking. The application of the method to yeast chromatin dynamics reveals different classes of constraints on mobility of telomeres, reflecting differences in nuclear envelope association. The generic nature of the software allows application to a variety of similar biological imaging tasks that require the extraction and quantitation of a moving particle's trajectory. +Affiliation +Biomedical Imaging Group, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland. daniel.sage@epfl.ch +Date-Added +2010-01-19 09:14:17 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +eng +Pmid +16190472 +Rating +0 +Local Files +Remote URLs + +Popko:2009p14958 +Automated Analysis of NeuronJ Tracing Data (article) +Author +Jonathan Popko and Adelaide Fernandes and Dora Brites and Lorene M Lanier +Journal +Cytom Part A +Year +2009 +Volume +75A +Number +4 +Pages +371--376 +Month +Jan +Keywords +Hippocampal-Neurons, Neuronj, Axon Guidance, Growth Cone, Polarity, Netrin-1, Laminin, Neurite Tracing, Imagej, Culture, Growth, Netrin +Abstract +Studies of neuronal differentiation in vitro often involve tracing and analysis of neurites. Neuron) (Meijering et al., Cytometry Part A 2004;58A:167-176; http://www.imagescience.org/meijering/software/neuronj/) is a program that can be used for semi-automated tracing of individual neurons; when tracing is completed, a text file containing neurite length measurements is generated. Using cultured hippocampal neurons, we have found that to reach statistical significance it is generally necessary to trace about 100 neurons in each treatment group. Posttracing data analysis requires importing each text file into a statistics program. Analysis of distinct parameters, such as effects of a treatment on axonal versus dendritic branching, requires a great deal of time consuming posttracing data manipulation. We have developed XL_Calculations, a Java-based program that performs batch analysis on Neuron) measurement files and automatically makes multiple calculations, including the number, length, and total output (sum length) of primary, secondary, and tertiary neurites on axons and dendrites, and writes the calculations into an Excel worksheet. Batch processing of Neuron) measurement files dramatically reduces the time required to analyze neuronal morphology. In addition, our program performs more than 45 distinct calculations, enabling detailed determination of treatment effects on neuronal differentiation. Using this program to analyze Neuron) tracing data, we demonstrate that continuous exposure of differentiating hippocampal neurons to Netrin 1 increases the number of secondary branches on both axons and dendrites, without significantly altering the length of the axon, dendrites, or branches. Similar results were obtained when neurons were grown on poly-D-lysine or laminin. (C) 2008 International Society far Advancement of Cytometry +Affiliation +Univ Minnesota, Dept Neurosci, Minneapolis, MN 55455 USA +Date-Added +2010-01-29 10:47:08 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/cyto.a.20660 +Language +English +Pmid +000264513800011 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/cyto.a.20660 + +Choi:2007p14905 +Open source, ImageJ based, web accessible tool for treatment plan evaluation (article) +Author +B Choi and C Nelson and Y Tsunashima and P Balter +Journal +Med Phys +Year +2007 +Volume +34 +Number +6 +Pages +2477--2477 +Month +Jan +Affiliation +Univ Texas, MD Anderson Canc Ctr, Houston, TX 77030 USA +Date-Added +2010-01-29 10:43:46 -0500 +Date-Modified +2012-06-07 09:36:36 -0400 +Doi +10.1118/1.2760991 +Language +English +Pmid +000247479600687 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1118/1.2760991 + +Kerner:2007p13995 +Root coverage assessment: validity and reproducibility of an image analysis system (article) +Author +Stéphane Kerner and Daniel Etienne and Jacques Malet and Francis Mora and Virginie Monnet-Corti and Philippe Bouchard +Journal +J Clin Periodontol +Year +2007 +Volume +34 +Number +11 +Pages +969--76 +Month +Nov +Keywords +Tooth Root, Epidemiologic Methods, Humans, Male, Tissue Transplantation, Adult, Gingival Recession, Photography: Dental, Middle Aged, Image Processing: Computer-Assisted, Female +Abstract +AIM: The aim of this methodological study was to validate a new method for root coverage evaluation following periodontal plastic surgery. MATERIAL AND METHODS: Thirty recessions were treated in 21 consecutive patients, using a subepithelial connective tissue graft technique. Clinical measurements and photographs were taken at baseline and 12+/-6 months after treatment. The mean percentage of root coverage for linear and surface area measurements was calculated using conventional clinical evaluation, and compared with ImageJ, a public domain Java image processing program. Bland-Altman plots were used for assessing repeatability and agreement between clinical and ImageJ measurements. The strength of the relationship was calculated using the Pearson product moment correlation coefficient. RESULTS: The repeatability of ImageJ was excellent for both linear and surface area measurements. The agreement between clinical and ImageJ measurements was good for the linear evaluation, showing lower and upper limits of -13.14% and 17.42%, respectively. Significant correlations (p<0.001) were found between clinical and ImageJ measurements, ranging from 0.93 to 0.94 for linear evaluation, and from 0.89 to 0.90 for surface evaluation. CONCLUSIONS: The outcomes of this study show that the ImageJ analysis is a reliable, reproducible method to evaluate the percentage of root coverage after periodontal plastic surgery, when a midfacial linear measurement is used. +Affiliation +Department of Periodontology, Service of Odontology, Hôtel-Dieu Hospital, AP-HP, Paris 7 - Denis Diderot University, U.F.R. of Odontology, Paris, France. +Date-Added +2010-01-19 09:14:52 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1600-051X.2007.01137.x +Language +eng +Pii +CPE1137 +Pmid +17877749 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1600-051X.2007.01137.x + +Mort:2009p13792 +Quantitative analysis of patch patterns in mosaic tissues with ClonalTools software (article) +Author +Richard L Mort +Journal +J Anat +Year +2009 +Volume +215 +Number +6 +Pages +698--704 +Month +Dec +Abstract +Quantitative analysis of mosaic tissues is a powerful method for following developmental lineages; however, analytical techniques are often subjective and repetitious. Here a flexible, semi-automated image analysis method for mosaic patterns is described. ClonalTools is a free customizable tool-set designed for the open-source image analysis package ImageJ. Circular, polygonal or linear one-dimensional mosaic arrays can be interrogated to provide measurements of the total number and width of positive and negative patches in a region of interest. These results are adjusted for the effects of random clumping using a previously described method to correct for differences in the contribution of the positive and negative cell type. The applicability of ClonalTools to different systems is discussed with reference to the analysis of mosaic patterns in the mouse corneal epithelium and adrenal cortex and in the outgrowth of neurites from explant cultures of mouse retina as example systems. To validate ClonalTools quantitatively, a recently published manual clonal analysis of the corneal epithelium of X-inactivation beta-Gal-mosaic mice was re-analysed. The semi-automated results did not differ significantly from the published data. Rapid quantification of such patterns to produce biologically relevant results represents a welcome improvement in terms of ease and speed of use over previous methods. +Affiliation +Division of Reproductive and Developmental Sciences, Genes and Development Group, The University of Edinburgh, Edinburgh, UK. richardm@hgu.mrc.ac.uk +Date-Added +2010-01-19 09:00:45 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1469-7580.2009.01150.x +Language +eng +Pii +JOA1150 +Pmid +19840025 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1469-7580.2009.01150.x + +Brown:2005p13955 +A cross-platform freeware tool for digital reconstruction of neuronal arborizations from image stacks (article) +Author +Kerry M Brown and Duncan E Donohue and Giampaolo D'Alessandro and Giorgio A Ascoli +Journal +Neuroinformatics +Year +2005 +Volume +3 +Number +4 +Pages +343--60 +Month +Jan +Keywords +Image Cytometry, Dendrites, Cerebellum, Hippocampus, Software, Pyramidal Cells, Cell Shape, Nervous System, Rats: Long-Evans, Axons, Neurons, Male, Rats, Animals, Female +Abstract +Digital reconstruction of neuronal arborizations is an important step in the quantitative investigation of cellular neuroanatomy. In this process, neurites imaged by microscopy are semi-manually traced through the use of specialized computer software and represented as binary trees of branching cylinders (or truncated cones). Such form of the reconstruction files is efficient and parsimonious, and allows extensive morphometric analysis as well as the implementation of biophysical models of electrophysiology. Here, we describe Neuron_ Morpho, a plugin for the popular Java application ImageJ that mediates the digital reconstruction of neurons from image stacks. Both the executable and code of Neuron_ Morpho are freely distributed (www.maths. soton.ac.uk/staff/D'Alessandro/morpho or www.krasnow.gmu.edu/L-Neuron), and are compatible with all major computer platforms (including Windows, Mac, and Linux). We tested Neuron_Morpho by reconstructing two neurons from each of the two preparations representing different brain areas (hippocampus and cerebellum), neuritic type (pyramidal cell dendrites and olivar axonal projection terminals), and labeling method (rapid Golgi impregnation and anterograde dextran amine), and quantitatively comparing the resulting morphologies to those of the same cells reconstructed with the standard commercial system, Neurolucida. None of the numerous morphometric measures that were analyzed displayed any significant or systematic difference between the two reconstructing systems. +Affiliation +Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030-4444, USA. +Date-Added +2010-01-19 09:12:53 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1385/NI:3:4:343 +Language +eng +Pii +NI:3:4:343 +Pmid +16284416 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1385/NI:3:4:343 + +Narro:2007p13898 +NeuronMetrics: software for semi-automated processing of cultured neuron images (article) +Author +Martha L Narro and Fan Yang and Robert Kraft and Carola Wenk and Alon Efrat and Linda L Restifo +Journal +Brain Res. +Year +2007 +Volume +1138 +Pages +57--75 +Month +Mar +Keywords +Cells: Cultured, Fluorescent Dyes, Automation, Neurites, Software, Central Nervous System, Drosophila, Animals, Neurons, Microscopy, Time Factors, Diagnostic Imaging +Abstract +Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of approximately 60 2D images is 1.0-2.5 h, from a folder of images to a table of numeric data. NeuronMetrics' output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery. +Affiliation +ARL Division of Neurobiology, University of Arizona, Tucson, AZ 85721, USA. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.brainres.2006.10.094 +Language +eng +Pii +S0006-8993(06)03215-X +Pmid +17270152 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.brainres.2006.10.094 + +Tian:2009p14897 +A new development of measurement of 19-Nortestosterone by combining immunochromatographic strip assay and ImageJ software (article) +Author +Zhuang Tian and Li Qiang Liu and Chifang Peng and Zhenxing Chen and Chuanlai Xu +Journal +Food Agr Immunol +Year +2009 +Volume +20 +Number +1 +Pages +1--10 +Month +Jan +Keywords +Calf Urine, Bovine Urine, Corticosteroids, Tandem Mass-Spectrometry, Residues, 19-Nortestosterone, Enzyme-Immunoassay, Anabolic-Steroids, Immunochromatography, Format, Glucuronides, Imagej, Liquid-Chromatography, Semi-Quantitative +Abstract +A rapid immunochromatographic assay was developed to detect 17-19-Nortestosterone (19-NT). The 19-NT-OVA conjugate was immobilised to nitrocellulose membrane as a test line and goat anti-rabbit IgG as a control line. Anti-19-NT polyclonal antibody labelled with colloidal gold particles acted as detector reagent. We tested the sensitivity of the strip using spiked swine urine, and analysed the intensity of test line using ImageJ software. The sensitivity by naked eye measurement was determined to be 200 ng/ml and lower limit using ImageJ was distinguished as 5 ng/ml. The total assay time was less than 20 min, suitable for screening and quantifying the residue of 19-NT in swine urine. +Affiliation +Jiangnan Univ, Sch Food Sci {\&} Technol, Wuxi, Jiangsu, Peoples R China +Date-Added +2010-01-29 10:43:45 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1080/09540100802621017 +Language +English +Pmid +000263715500001 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1080/09540100802621017 + +Bell:2005p15142 +EarthTutor: An Interactive Intelligent Tutoring System for Remote Sensing (article) +Author +A M Bell and K Parton and E Smith +Journal +American Geophysical Union +Year +2005 +Volume +52 +Pages +08 +Month +Dec +Keywords +0820 Curriculum and laboratory design, 0845 Instructional tools, 0855 Diversity, 0805 Elementary and secondary education, 0825 Teaching methods +Abstract +Earth science classes in colleges and high schools use a variety of satellite image processing software to teach earth science and remote sensing principles. However, current tutorials for image processing software are often paper-based or lecture-based and do not take advantage of the full potential of the computer context to teach, immerse, and stimulate students. We present EarthTutor, an adaptive, interactive Intelligent Tutoring System (ITS) being built for NASA (National Aeronautics and Space Administration) that is integrated directly with an image processing application. The system aims to foster the use of satellite imagery in classrooms and encourage inquiry-based, hands-on earth science scientific study by providing students with an engaging imagery analysis learning environment. EarthTutor's software is available as a plug-in to ImageJ, a free image processing system developed by the NIH (National Institute of Health). Since it is written in Java, it can be run on almost any platform and also as an applet from the Web. Labs developed for EarthTutor combine lesson content (such as HTML web pages) with interactive activities and questions. In each lab the student learns to measure, calibrate, color, slice, plot and otherwise process and analyze earth science imagery. During the activities, EarthTutor monitors students closely as they work, which allows it to provide immediate feedback that is customized to a particular student's needs. As the student moves through the labs, EarthTutor assesses the student, and tailors the presentation of the content to a student's demonstrated skill level. EarthTutor's adaptive approach is based on emerging Artificial Intelligence (AI) research. Bayesian networks are employed to model a student's proficiency with different earth science and image processing concepts. Agent behaviors are used to track the student's progress through activities and provide guidance when a student encounters difficulty. Through individual feedback and adaptive instruction, EarthTutor aims to offer the benefits of a one-on-one human instructor in a cost-effective, easy-to-use application. We are currently working with remote sensing experts to develop EarthTutor labs for diverse earth science subjects such as global vegetation, stratospheric ozone, oceanography, polar sea ice and natural hazards. These labs will be packaged with the first public release of EarthTutor in December 2005. Custom labs can be designed with the EarthTutor authoring tool. The tool is basic enough to allow teachers to construct tutorials to fit their classroom's curriculum and locale, but also powerful enough to allow advanced users to create highly-interactive labs. Preliminary results from an ongoing pilot study demonstrate that the EarthTutor system is effective and enjoyable teaching tool, relative to traditional satellite imagery teaching methods. +Affiliation +AA(Stottler Henke Associates, Inc., 951 Mariner's Island Blvd Suite 360, San Mateo, CA 94404 United States ; bell@stottlerhenke.com), AB(Stottler Henke Associates, Inc., 951 Mariner's Island Blvd Suite 360, San Mateo, CA 94404 United States ; parton@stottlerhenke.com), AC(Department of Ocean, Earth and Atmospheric Sciences Old Dominion University, 768 W52nd Street, Crittenton Hall, Room 124 Old Dominion University, Norfolk, VA 23529 United States ; exsmith@odu.edu) +Date-Added +2010-01-29 10:58:36 -0500 +Date-Modified +2011-07-06 15:21:14 -0400 +Note +(c) 2005: American Geophysical Union +Pmid +2005AGUFMED52A..08B +Rating +0 +Local Files +Remote URLs +http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005AGUFMED52A..08B&link_type=ABSTRACT + +Vrekoussis:2009p13795 +Image analysis of breast cancer immunohistochemistry-stained sections using ImageJ: an RGB-based model (article) +Author +T Vrekoussis and V Chaniotis and I Navrozoglou and V Dousias and K Pavlakis and E N Stathopoulos and O Zoras +Journal +Anticancer Res +Year +2009 +Volume +29 +Number +12 +Pages +4995--8 +Month +Dec +Abstract +BACKGROUND: Image analysis of tissue sections using RGB image profiling is a modern accepted technique. MATERIALS AND METHODS: A new method of RGB analysis, using the freeware ImageJ, is presented which can be applied to sections with either nuclear or cytoplasmic staining. The step-by-step process is presented and the method is tested using breast cancer specimens immunostained for CK-19 and estrogen receptors. RESULTS: This image analysis easily discriminates CK-19 and estrogen receptor positivity in prepared breast cancer specimens. The method is easy to perform, without the need for previous image transformations. CONCLUSION: Compared to previous methods, this method proved more accurate in estimating the actual colours that an observer recognizes as positive after immunostaining. Further studies are needed to evaluate whether this method is efficient enough to be applied in clinical practice. +Affiliation +Department of Obstetrics and Gynecology, Medical School, University of Ioannina, Ioannina, Greece. +Date-Added +2010-01-19 09:02:48 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +eng +Pii +29/12/4995 +Pmid +20044607 +Rating +0 +Local Files +Remote URLs + +Saalfeld:2009p15535 +CATMAID: collaborative annotation toolkit for massive amounts of image data (article) +Author +Stephan Saalfeld and Albert Cardona and Volker Hartenstein and Pavel Tomancák +Journal +Bioinformatics +Year +2009 +Volume +25 +Number +15 +Pages +1984--6 +Month +Aug +Keywords +Algorithms, Computational Biology, Computer Graphics, Software, Information Storage and Retrieval, Databases: Factual, Imaging: Three-Dimensional, Database Management Systems +Abstract +SUMMARY: High-resolution, three-dimensional (3D) imaging of large biological specimens generates massive image datasets that are difficult to navigate, annotate and share effectively. Inspired by online mapping applications like GoogleMaps, we developed a decentralized web interface that allows seamless navigation of arbitrarily large image stacks. Our interface provides means for online, collaborative annotation of the biological image data and seamless sharing of regions of interest by bookmarking. The CATMAID interface enables synchronized navigation through multiple registered datasets even at vastly different scales such as in comparisons between optical and electron microscopy. AVAILABILITY: http://fly.mpi-cbg.de/catmaid. +Affiliation +Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. +Date-Added +2010-01-29 11:12:34 -0500 +Date-Modified +2012-06-06 23:04:38 -0400 +Doi +10.1093/bioinformatics/btp266 +Language +eng +Pii +btp266 +Pmid +19376822 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1093/bioinformatics/btp266 + +Picht:2007p14799 +SparkMaster: automated calcium spark analysis with ImageJ (article) +Author +Eckard Picht and Aleksey V Zima and Lothar A Blatter and Donald M Bers +Journal +Am J Physiol, Cell Physiol +Year +2007 +Volume +293 +Number +3 +Pages +C1073--81 +Month +Sep +Keywords +Algorithms, Mice, Cats, Reproducibility of Results, Animals, Software, Myocytes: Smooth Muscle, Myocytes: Cardiac, Muscle Fibers: Skeletal, Sarcoplasmic Reticulum, Male, Female, Calcium, Calcium Signaling, Predictive Value of Tests, Microscopy: Confocal +Abstract +Ca sparks are elementary Ca-release events from intracellular Ca stores that are observed in virtually all types of muscle. Typically, Ca sparks are measured in the line-scan mode with confocal laser-scanning microscopes, yielding two-dimensional images (distance vs. time). The manual analysis of these images is time consuming and prone to errors as well as investigator bias. Therefore, we developed SparkMaster, an automated analysis program that allows rapid and reliable spark analysis. The underlying analysis algorithm is adapted from the threshold-based standard method of spark analysis developed by Cheng et al. (Biophys J 76: 606-617, 1999) and is implemented here in the freely available image-processing software ImageJ. SparkMaster offers a graphical user interface through which all analysis parameters and output options are selected. The analysis includes general image parameters (number of detected sparks, spark frequency) and individual spark parameters (amplitude, full width at half-maximum amplitude, full duration at half-maximum amplitude, full width, full duration, time to peak, maximum steepness of spark upstroke, time constant of spark decay). We validated the algorithm using images with synthetic sparks embedded into backgrounds with different signal-to-noise ratios to determine an analysis criteria at which a high sensitivity is combined with a low frequency of false-positive detections. Finally, we applied SparkMaster to analyze experimental data of sparks measured in intact and permeabilized ventricular cardiomyocytes, permeabilized mammalian skeletal muscle, and intact smooth muscle cells. We found that SparkMaster provides a reliable, easy to use, and fast way of analyzing Ca sparks in a wide variety of experimental conditions. +Affiliation +Dept. of Physiology, Loyola Univ. Chicago, Stritch School of Medicine, 2160 South First Ave., Maywood, IL 60153, USA. +Date-Added +2010-01-28 21:12:08 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1152/ajpcell.00586.2006 +Language +eng +Pii +00586.2006 +Pmid +17376815 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1152/ajpcell.00586.2006 + +Medeiros:2009p13893 +Novel sequential ChIP and simplified basic ChIP protocols for promoter co-occupancy and target gene identification in human embryonic stem cells (article) +Author +Ricardo B Medeiros and Kate J Papenfuss and Brian Hoium and Kristen Coley and Joy Jadrich and Saik-Kia Goh and Anuratha Elayaperumal and Julio E Herrera and Ernesto Resnik and Hsiao-Tzu Ni +Journal +BMC Biotechnol +Year +2009 +Volume +9 +Pages +59 +Month +Jan +Keywords +Cell Line, Embryonic Stem Cells, Software, Reverse Transcriptase Polymerase Chain Reaction, Mice, Sensitivity and Specificity, Animals, Chromatin Immunoprecipitation, Humans +Abstract +BACKGROUND: The investigation of molecular mechanisms underlying transcriptional regulation, particularly in embryonic stem cells, has received increasing attention and involves the systematic identification of target genes and the analysis of promoter co-occupancy. High-throughput approaches based on chromatin immunoprecipitation (ChIP) have been widely used for this purpose. However, these approaches remain time-consuming, expensive, labor-intensive, involve multiple steps, and require complex statistical analysis. Advances in this field will greatly benefit from the development and use of simple, fast, sensitive and straightforward ChIP assay and analysis methodologies. RESULTS: We initially developed a simplified, basic ChIP protocol that combines simplicity, speed and sensitivity. ChIP analysis by real-time PCR was compared to analysis by densitometry with the ImageJ software. This protocol allowed the rapid identification of known target genes for SOX2, NANOG, OCT3/4, SOX17, KLF4, RUNX2, OLIG2, SMAD2/3, BMI-1, and c-MYC in a human embryonic stem cell line. We then developed a novel Sequential ChIP protocol to investigate in vivo promoter co-occupancy, which is basically characterized by the absence of antibody-antigen disruption during the assay. It combines centrifugation of agarose beads and magnetic separation. Using this Sequential ChIP protocol we found that c-MYC associates with the SOX2/NANOG/OCT3/4 complex and identified a novel RUNX2/BMI-1/SMAD2/3 complex in BG01V cells. These two TF complexes associate with two distinct sets of target genes. The RUNX2/BMI-1/SMAD2/3 complex is associated predominantly with genes not expressed in undifferentiated BG01V cells, consistent with the reported role of those TFs as transcriptional repressors. CONCLUSION: These simplified basic ChIP and novel Sequential ChIP protocols were successfully tested with a variety of antibodies with human embryonic stem cells, generated a number of novel observations for future studies and might be useful for high-throughput ChIP-based assays. +Affiliation +Dept, Antibody Applications and Stem Cells, R{\&}D Systems, Inc,, Minneapolis-MN, USA. ricardo.demedeiros@rndsystems.com +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1186/1472-6750-9-59 +Language +eng +Pii +1472-6750-9-59 +Pmid +19563662 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1186/1472-6750-9-59 + +Papadopulos:2007p13902 +Common tasks in microscopic and ultrastructural image analysis using ImageJ (article) +Author +Francesca Papadopulos and Matthew Spinelli and Sabrina Valente and Laura Foroni and Catia Orrico and Francesco Alviano and Gianandrea Pasquinelli +Journal +Ultrastruct Pathol +Year +2007 +Volume +31 +Number +6 +Pages +401--7 +Month +Jan +Keywords +Immunohistochemistry, Cooperative Behavior, Software, Rats, Female, Image Processing: Computer-Assisted, Animals, Microscopy: Electron: Transmission, Humans +Abstract +Cooperation between research communities and software-development teams has led to the creation of novel software. The purpose of this paper is to show an alternative work method based on the usage of ImageJ (http://rsb.info.nih.gov/ij/), which can be effectively employed in solving common microscopic and ultrastructural image analysis tasks. As an open-source software, ImageJ provides the possibility to work in a free-development/sharing world. Its very "friendly" graphical user interface helps users to manage and edit biomedical images. The on-line material such as handbooks, wikis, and plugins leads users through various functions, giving clues about potential new applications. ImageJ is not only a morphometric analysis software, it is sufficiently flexible to be adapted to the numerous requirements tasked in the laboratories as routine as well as research demands. Examples include area measurements on selectively stained tissue components, cell count and area measurements at single cell level, immunohistochemical antigen quantification, and immunoelectron microscopy gold particle count. +Affiliation +Department of Experimental Pathology, Clinical Pathology Section, University of Bologna, Bologna, Italy. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1080/01913120701719189 +Language +eng +Pii +788723637 +Pmid +18098058 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1080/01913120701719189 + +Kirilova:2008p14991 +Three-dimensional motion of liver tumors using cine-magnetic resonance imaging (article) +Author +Anna Kirilova and Gina Lockwood and M Math and Perry Choi and Neelufer Bana and Masoom A Haider and Kristy K Brock and Cynthia Eccles and Laura A Dawson +Journal +Int J Radiat Oncol +Year +2008 +Volume +71 +Number +4 +Pages +1189--1195 +Month +Jan +Keywords +Lung, Dose-Escalation, Radiotherapy, Organ Motion, Hepatobiliary Cancer, Liver Metastases, Movement, Cine-Mri, Computed-Tomography, Respiratory Organ Motion, Real-Time Tumor, Tracking, Position +Abstract +Purpose: To measure the three-dimensional motion of liver tumors using cine-magnetic resonance imaging (MRI) and compare it to the liver motion assessed using fluoroscopy.Methods and Materials: Liver and liver tumor motion were investigated in the first 36 patients with primary (n = 20) and metastatic (n = 16) liver cancer accrued to our Phase I stereotactic radiotherapy study. At simulation, all patients underwent anteroposterior fluoroscopy, and the maximal diaphragm excursion in the craniocaudal (CC) direction was observed. Cine-MRI using T-2-weighted single shot fast spin echo sequences were acquired in three orthogonal planes during free breathing through the centroid of the most dominant liver tumor. ImageJ software was used to measure the maximal motion of the tumor edges in each plane. The intra- and interobserver reproducibility was also quantified.Results: The average CC motion of the liver at fluoroscopy was 15 mm (range, 5-41). On cine-MRI, the average CC tumor motion was 15.5 mm (range, 6.9-35.4), the anteroposterior motion was 10 mm (range, 3.7-21.6), and the mediolateral motion was 7.5 mm (range, 3.8-14.8). The fluoroscopic CC diaphragm motion did not correlate well with the MRI CC tumor motion (r = 0.25). The mean intraobserver error was <2 mm in the CC, anteroposterior, and mediolateral directions, and 90% of measurements between observers were within 3 mm.Conclusions: The results of our study have shown that cine-MRI can be used to directly assess liver tumor motion in three dimensions. Tumor motion did not correlate well with the diaphragm motion measured using kilovoltage fluoroscopy. The tumor motion data from cine-MRI can be used to facilitate individualized planning target volume margins to account for breathing motion. (C) 2008 Elsevier Inc. +Affiliation +Univ Toronto, Princess Margaret Hosp, Dept Radiat Phys, Toronto, ON M5G 2M9, Canada +Date-Added +2010-01-29 10:52:00 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.ijrobp.2007.11.026 +Language +English +Pmid +000257299200030 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.ijrobp.2007.11.026 + +Tong:2009p13815 +Motion-based angiogenesis analysis: a simple method to quantify blood vessel growth (article) +Author +Edmund Y Tong and Geoffrey C Collins and April E Greene-Colozzi and Julia L Chen and Philip D Manos and Kyle M Judkins and Joseph A Lee and Michael J Ophir and Farrah M Laliberte and Timothy J Levesque +Journal +Zebrafish +Year +2009 +Volume +6 +Number +3 +Pages +239--43 +Month +Sep +Keywords +Microscopy: Video, Angiogenesis Inhibitors, Vascular Endothelial Growth Factor A, Fibroblast Growth Factor 2, Neovascularization: Physiologic, Zebrafish, Software, Animals +Abstract +Existing methods to quantify angiogenesis range from image analysis of photographs to fluorescent microscopy. These methods are often time consuming and costly; they also may not detect capillaries if they are indistinct from the background of the image. We have developed a simple method based on the motion of blood to create an image that reveals the entire angiogenic vasculature. Two image analysis software programs were used separately to demonstrate the method. Using either ImageJ or Environment for Visualizing Images, we analyzed a video clip of regenerated tissue from the partially amputated caudal fin of a zebrafish (Danio rerio). The deviations among the frames in the video stack were calculated to reveal pixels where motion has occurred. The resulting image highlighted all vessels through which blood flowed and allowed for automatic quantification of the newly developed vasculature. Using this method, we quantified the angiogenic action of basic fibroblast growth factor and vascular endothelial growth factor, as well as suppression of angiogenesis by an inhibitor. In a preliminary study, we also found that it could be used to trace the developing vasculature in zebrafish embryos. Thus, motion-based angiogenesis analysis may provide an easy and accurate quantification of angiogenesis. +Affiliation +Department of Biology, Wheaton College, Norton, Massachusetts 02766, USA. etong@wheatoncollege.edu +Date-Added +2010-01-19 09:07:31 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1089/zeb.2008.0554 +Language +eng +Pmid +19566407 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1089/zeb.2008.0554 + +Chinga:2007p13951 +Quantification of the 3D microstructure of SC surfaces (article) +Author +Gary Chinga and Per Olav Johnsen and Robert Dougherty and Elisabeth Lunden Berli and Joachim Walter +Journal +Journal of microscopy +Year +2007 +Volume +227 +Number +Pt 3 +Pages +254--65 +Month +Sep +Abstract +This study presents the development of an ImageJ plugin for surface characterization. Based on gradient analysis, parameters, such as the gradient magnitude, orientation, mean resultant vector and surface area are derived. A comparative study of supercalendered (SC) papers was performed to verify the surface representations yielded by a laser profilometer. The surface representations of samples covered with carbon and gold were compared to untreated samples. The results confirm the suitability of gold coating for reducing the artefacts encountered on laser profilometry surface representations of paper. In addition, a complete scanning electron microscopy analysis is performed on the assessed samples to quantify the surface fraction covered by mineral fillers and to reveal the true 3D microstructure of SC surfaces. The influence of filler coverage and filler type on the gloss level of commercial SC papers is evaluated. The relationship between the surface topography, gloss and PPS roughness for a series of commercial SC papers is established. +Affiliation +Paper and Fibre Research Institute, N-7491 Trondheim, Norway. gary.chinga@pfi.no +Date-Added +2010-01-19 09:12:42 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1365-2818.2007.01809.x +Language +eng +Pii +JMI1809 +Pmid +17760621 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1365-2818.2007.01809.x + +Gottsch:2006p13999 +Analysis and documentation of progression of Fuchs corneal dystrophy with retroillumination photography (article) +Author +John D Gottsch and Olof H Sundin and Erik V Rencs and David G Emmert and Walter J Stark and Clement J Cheng and Gregory W Schmidt +Journal +Cornea +Year +2006 +Volume +25 +Number +4 +Pages +485--9 +Month +May +Keywords +Fuchs' Endothelial Dystrophy, Photography, Disease Progression, Image Processing: Computer-Assisted, Humans, Diagnostic Techniques: Ophthalmological +Abstract +PURPOSE: Fuchs corneal dystrophy (FCD) is a degenerative disorder of the cornea that is characterized by the progressive accumulation of guttae, which are small excrescences of Descemet's membrane. We describe a method for documenting the location and number of guttae, and ask whether disease progression can be observed during relatively short periods. METHODS: Patients with FCD were imaged by standard retroillumination photography with a slit lamp. Scanned photographs were analyzed by using NIH ImageJ software to determine the number of individual guttae and areas of confluence. RESULTS: In 4 FCD patients, photographs taken 23 to 30 months apart revealed that, once formed, individual guttae and their relative positions persisted during this period. Very few guttae disappeared, and the emergence of many new guttae was observed. Determination of the area with confluent guttae was used to quantify disease stage. CONCLUSIONS: Computer-assisted analysis of retroillumination photographs is proposed as an effective way to document the number and distribution of individual guttae. Although the disease typically progresses slowly during decades, we have been able to detect the formation of new guttae within only 2 years. This rapid assessment of disease progression could be used to measure phenotypic differences between genetic subtypes of FCD. It also could provide important baseline information and methodology for clinical trials of therapeutic options, should these become available. +Affiliation +Center for Corneal Genetics, Cornea and External Disease Service, The Wilmer Eye Institute, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. jgottsch@jhmi.edu +Date-Added +2010-01-19 09:14:10 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1097/01.ico.0000178726.11693.14 +Language +eng +Pii +00003226-200605000-00023 +Pmid +16670493 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1097/01.ico.0000178726.11693.14 + +Shihana:2009p13804 +A Simple Quantitative Bedside Test to Determine Methemoglobin (article) +Author +Fathima Shihana and Dhammika Menike Dissanayake and Nicholas Allan Buckley and Andrew Hamilton Dawson +Journal +Ann Emerg Med +Year +2009 +Month +Oct +Abstract +STUDY OBJECTIVE: Methemoglobinemia after pesticide poisoning is associated with a mortality of 12% in Sri Lanka. Treatment is complicated by the lack of laboratory facilities. We aimed to develop and validate a low-cost bedside test for quantitative estimation of clinically significant methemoglobin to be used in settings of limited resources. METHODS: A method to reliably produce blood samples with 10% to 100% methemoglobin was developed. Freshly prepared methemoglobin samples were used to develop the color chart. One drop (10 muL) of prepared methemoglobin sample was placed on white absorbent paper and scanned using a flatbed Cannon Scan LiDE 25 scanner. The mean red, green, and blue values were measured with ImageJ 1.37v. These color values were used to prepare a color chart to be used at the bedside. Interobserver agreement was assessed against prepared samples. The results from clinical use were compared with formal methemoglobin measurements. RESULTS: The red color value was linearly related to percentage methemoglobin (R(2)=0.9938), with no effect of absolute hemoglobin concentration. Mean interobserver (N=21) agreement and weighted kappa for scanned methemoglobin spots using the color chart were 94% and 0.83, respectively. Mean interobserver (N=9) agreement and weighted kappa for a freshly prepared methemoglobin sample with the chart were 88% and 0.71, respectively. Clinical use of the color chart also showed good agreement with spectrometric measurements. CONCLUSION: A color chart can be used to give a clinically useful quantitative estimate of methemoglobinemia. +Affiliation +South Asian Clinical Toxicology Research Collaboration, Faculty of Medicine, University of Peradeniya, Sri Lanka; Department of Pathology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka. +Date-Added +2010-01-19 09:05:24 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.annemergmed.2009.07.022 +Language +ENG +Pii +S0196-0644(09)01281-5 +Pmid +19818531 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.annemergmed.2009.07.022 + +Sole:2007p13954 +A new method based on image analysis for determining cyanobacterial biomass by CLSM in stratified benthic sediments (article) +Author +A Solé and J Mas and I Esteve +Journal +Ultramicroscopy +Year +2007 +Volume +107 +Number +8 +Pages +669--73 +Month +Aug +Keywords +Geologic Sediments, Image Processing: Computer-Assisted, Biomass, Cyanobacteria, Microscopy: Confocal +Abstract +Cyanobacteria are the dominant primary producers in microbial mats, which are stratified benthic microbial ecosystems found in coastal environments. Some cyanobacteria form long filaments, which make difficult to apply classical methods to estimate their biomass because they establish strong interactions with detritic particles. In a previous study, we described a method for determining cyanobacterial biomass by means of confocal laser scanning microscopy (CLSM). However, the manual method used, based on summa projection images, was difficult to apply when analyzing a large number of samples. In this paper, we described a new automated method, based on stacks and applying the plugin voxel counter in the ImageJ analysis system, more adequate for obtaining biomass data quickly from a large number of CLSM images. +Affiliation +Department of Genetics and Microbiology, Autonomous University of Barcelona, Bellaterra, 08193 Barcelona, Spain. antoni.sole@uab.es +Date-Added +2010-01-19 09:13:00 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.ultramic.2007.01.007 +Language +eng +Pii +S0304-3991(07)00007-1 +Pmid +17350172 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.ultramic.2007.01.007 + +Cathelin:2007p14913 +AGScan: a pluggable microarray image quantification software based on the ImageJ library (article) +Author +R Cathelin and F Lopez and Ch Klopp +Journal +Bioinformatics +Year +2007 +Volume +23 +Number +2 +Pages +247--248 +Month +Jan +Abstract +Many different programs are available to analyze microarray images. Most programs are commercial packages, some are free. In the latter group only few propose automatic grid alignment and batch mode. More often than not a program implements only one quantification algorithm. AGScan is an open source program that works on all major platforms. It is based on the ImageJ library [Rasband (1997-2006)] and offers a plug-in extension system to add new functions to manipulate images, align grid and quantify spots. It is appropriate for daily laboratory use and also as a framework for new algorithms. +Affiliation +INRA, Sigenae, UR875, F-31326 Castanet Tolosan, France +Date-Added +2010-01-29 10:43:46 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1093/bioinformatics/btl564 +Language +English +Pmid +000243992400056 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1093/bioinformatics/btl564 + +Ropolo:2006p14010 +Automated quality control in computed radiography (article) +Author +R Ropolo and O Rampado and P Isoardi and A Izzo and L Savio and T Cammarota and O Davini and R De Lucchi and G Gandini +Journal +Radiol Med +Year +2006 +Volume +111 +Number +8 +Pages +1156--67 +Month +Dec +Keywords +Humans, Practice Guidelines as Topic, Cost-Benefit Analysis, Italy, Image Processing: Computer-Assisted, Quality Assurance: Health Care, Radiographic Image Interpretation: Computer-Assisted, Algorithms, Quality Control +Abstract +PURPOSE: The purpose of this paper is to describe the automation of quality control procedures on photo-stimulable imaging plates by means of an image-processing tool providing automatic reading of the images and automatic calculation of the quality parameters monitored. MATERIALS AND METHODS: Quality-control procedures were performed according to the main available guidelines. The quality assurance programme was applied to several Kodak and Philips devices in four radiological departments. The automatic image-processing tool was developed using public domain software (Java-based ImageJ software) and contains both reading and computation procedures. RESULTS: The quality checks and algorithms described were successfully applied, proving useful for identification of defective plates and for implementation of the quality assurance programme. The use of automation allowed significant savings in the time required for quality checks. CONCLUSIONS: Completely automated image reading allows substantial economic and human resources savings, as it eliminates much of the transfer, reproduction, processing and filing procedures. +Affiliation +ASO San Giovanni Battista, C.so Bramante 88, I-10126, Torino (TO). rropolo@molinette.piemonte.it +Date-Added +2010-01-19 09:19:22 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s11547-006-0113-5 +Language +ita +Pmid +17171519 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s11547-006-0113-5 + +Lindley:2009p13820 +Properties of secondary and tertiary human enteric nervous system neurospheres (article) +Author +Richard M Lindley and Daniel B Hawcutt and M Gwen Connell and David H Edgar and Simon E Kenny +Journal +J Pediatr Surg +Year +2009 +Volume +44 +Number +6 +Pages +1249-55; discussion 1255--6 +Month +Jun +Keywords +Enteric Nervous System, Hirschsprung Disease, Stem Cell Transplantation, Mice, Stem Cells, Animals, Humans +Abstract +Advances in enteric nervous system (ENS) stem cell biology have raised the possibility of treating Hirschsprung's disease with ENS stem/progenitor cell (ENSPC) transplantation. This study aimed to expand ENSPC numbers by the growth and redissociation of neurospheres and assess their differential potential. METHODS: Human ENS neurospheres were cultured as previously described and redissociated to generate secondary and tertiary neurospheres. Neurospheres were assessed for the presence of neuronal (PGP9.5), glial (S100), and stem cell (p75, nestin markers). The degree of immunofluorescence was quantified using the ImageJ program. Secondary/tertiary neurospheres were transplanted into mouse distal colon grown in tissue culture. RESULTS: Secondary/tertiary neurospheres could be generated with exponentially increasing numbers. Tertiary neurospheres showed a significant increase in the proportion of p75 staining but a significant decrease in the proportion of S100 staining. After transplantation, secondary/tertiary neurosphere-derived cells positive for PGP9.5 and S100 could be identified. CONCLUSIONS: It is possible to exponentially expand neurosphere and therefore ENSPC numbers by repeated dissociation and culture. There is a loss of S100-positive cells in secondary/tertiary neurospheres, but the ENSPCs remain capable of differentiating into neurons and glia when transplanted into an embryonic gut environment. +Affiliation +Department of Paediatric Surgery, Queens's Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK. +Date-Added +2010-01-19 09:08:41 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jpedsurg.2009.02.048 +Language +eng +Pii +S0022-3468(09)00195-X +Pmid +19524749 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jpedsurg.2009.02.048 + +HachetHaas:2006p14805 +FRET and colocalization analyzer--a method to validate measurements of sensitized emission FRET acquired by confocal microscopy and available as an ImageJ Plug-in (article) +Author +Muriel Hachet-Haas and Noël Converset and Olivier Marchal and Hans Matthes and Sophie Gioria and Jean-Luc Galzi and Sandra Lecat +Journal +Microsc. Res. Tech. +Year +2006 +Volume +69 +Number +12 +Pages +941--56 +Month +Dec +Keywords +Microscopy: Confocal, Receptors: G-Protein-Coupled, Software, Fluorescent Dyes, Arrestins, Image Processing: Computer-Assisted, Fluorescence Resonance Energy Transfer, Humans +Abstract +Fluorescence resonance energy transfer (FRET) between an adequate pair of fluorophores is an indication of closer proximity than colocalization and is used by biologists to study fluorescently modified protein interactions inside cells. We present a method for visualization of FRET images acquired by confocal sensitized emission, involving excitation of the donor fluorophore and detection of the energy transfer as an emission from the acceptor fluorophore into the FRET channel. Authentic FRET signal measurements require the correction from the FRET channel of the undesired bleed-through signals (BT) resulting from both the leak-through of the donor emission and the direct acceptor emission. Our method reduces the interference of the user to a minimum by analyzing the entire image, pixel by pixel. It proposes imaging treatments and the display of control images to validate the BT calculation and the image corrections. It displays FRET images as a function of the colocalization of the two fluorescent partners. Finally, it proposes an alternative to normalization of the FRET intensities to compare FRET signal variations between samples. This method called "FRET and Colocalization Analyzer" has been implemented in a Plug-in of the freely available ImageJ software. It is particularly adapted when transient expression of the fluorescent proteins is used thereby giving very variable expression levels or when the colocalization of the two partners is varying in proportion, in amount, and in size, as a function of time. The method and program are validated using the analysis of the spatio-temporal interactions between a G-protein coupled receptor, the tachykinin NK2 receptor, and the beta-arrestin 2 as an example. +Affiliation +Département Récepteurs et Protéines Membranaires, Institut Gilbert-Laustriat, UMR 7175 CNRS/Université-Strasbourg I, BP10413, F-67412 ILLKIRCH Cedex, France. +Date-Added +2010-01-28 21:12:09 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/jemt.20376 +Language +eng +Pmid +17080432 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/jemt.20376 + +Lau:2005p14012 +Computer-assisted image analysis of bronchioloalveolar carcinoma (article) +Author +Derick Lau and Anthony Seibert and David Gandara and Luko Laptalo and Este Geraghty and Christopher Coulon +Journal +Clin Lung Cancer +Year +2005 +Volume +6 +Number +5 +Pages +281--6 +Month +Mar +Keywords +Remission Induction, Humans, Antineoplastic Agents, Image Processing: Computer-Assisted, Tomography: X-Ray Computed, Quinazolines, Adenocarcinoma: Bronchiolo-Alveolar, Lung Neoplasms +Abstract +In clinical trials, response rate is an important endpoint for assessing the efficacy of an anticancer drug. The Response Evaluation Criteria for Solid Tumors (RECIST) has been widely used as a standard method to assess response. The RECIST requires only 1-dimensional measurement of tumor size. However, bronchioloalveolar carcinoma (BAC), which commonly presents as infiltrative or micronodular lesions, is not always readily assessable by RECIST. During the past 2 years, we have been developing computer-based programs to more accurately measure tumor size on chest computed tomography (CT) scans. In a first-generation computer-assisted image analysis (CAIA) system, we were able to capture and quantify lesions on CT scans by linking the software programs of eFilm, HyperSnap, and Scion. We have applied this CAIA approach to measuring BAC response to gefitinib in the Southwest Oncology Group (S0126) trial. However, this first-generation CAIA system involves multiple manual steps and is therefore labor intensive. We are now developing a fully automated CAIA program based on a versatile software platform, ImageJ, created at the National Institutes of Health. Taking theoretical and physical considerations into account, Java plug-in programs for ImageJ are created to automatically analyze CT scans in the Digital Imaging and Communications in Medicine format. We have demonstrated the feasibility of an ImageJ-based automated CAIA program for measuring BAC bidimensionally on CT scans. This automated CAIA system will be applied in a prospective clinical trial of the GVAX vaccine in patients with BAC. +Affiliation +University of California Davis Cancer Center, Sacramento, CA 95817, USA. derick.lau@ucdmc.ucdavis.edu +Date-Added +2010-01-19 09:18:14 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +eng +Pmid +15845178 +Rating +0 +Local Files +Remote URLs + +Burger:2008p14082 +Digital image processing: An algorithmic introduction using Java (book) +Publisher +ISBN 978-1-84628-379-6, Springer +Year +2008 +Author +Wilhelm Burger and Mark James Burge +Month +Jan +Keywords +Computers +Abstract +C.2 API The complete documentation and source code for the Both are extremely helpful resources for developing new plugins, +Date-Added +2010-01-28 21:21:51 -0500 +Date-Modified +2012-06-07 09:33:23 -0400 +Pmid +jCEi9MVfxD8C +Rating +0 +Url +http://www.imagingbook.com/ +Local Files +Remote URLs +http://books.google.com/books?id=jCEi9MVfxD8C&printsec=frontcover +http://www.imagingbook.com/ + +Bolte:2006p2466 +A guided tour into subcellular colocalization analysis in light microscopy (article) +Author +S Bolte and F P Cordelières +Journal +Journal of microscopy +Year +2006 +Volume +224 +Number +Pt 3 +Pages +213--32 +Month +Nov +Abstract +It is generally accepted that the functional compartmentalization of eukaryotic cells is reflected by the differential occurrence of proteins in their compartments. The location and physiological function of a protein are closely related; local information of a protein is thus crucial to understanding its role in biological processes. The visualization of proteins residing on intracellular structures by fluorescence microscopy has become a routine approach in cell biology and is increasingly used to assess their colocalization with well-characterized markers. However, image-analysis methods for colocalization studies are a field of contention and enigma. We have therefore undertaken to review the most currently used colocalization analysis methods, introducing the basic optical concepts important for image acquisition and subsequent analysis. We provide a summary of practical tips for image acquisition and treatment that should precede proper colocalization analysis. Furthermore, we discuss the application and feasibility of colocalization tools for various biological colocalization situations and discuss their respective strengths and weaknesses. We have created a novel toolbox for subcellular colocalization analysis under ImageJ, named JACoP, that integrates current global statistic methods and a novel object-based approach. +Affiliation +Plateforme d'Imagerie et de Biologie Cellulaire, IFR 87 la Plante et son Environnement, Institut des Sciences du Végétal, Avenue de la Terrasse, 91198 Gif-sur-Yvette Cedex, France. Susanne.Bolte@isv.cnrs-gif.fr +Date-Added +2007-12-28 06:46:39 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1365-2818.2006.01706.x +Language +eng +Pii +JMI1706 +Pmid +17210054 +Rating +0 +Read +Yes +Local Files + +Remote URLs +http://dx.doi.org/10.1111/j.1365-2818.2006.01706.x + +Stepensky:2007p13900 +FRETcalc plugin for calculation of FRET in non-continuous intracellular compartments (article) +Author +David Stepensky +Journal +Biochem. Biophys. Res. Commun. +Year +2007 +Volume +359 +Number +3 +Pages +752--8 +Month +Aug +Keywords +Genes: Reporter, Fluorescence Resonance Energy Transfer, Humans, Endoplasmic Reticulum, Hela Cells +Abstract +FRET has emerged as an important tool for studying intracellular processes and interactions between biomolecules. Intracellular donor and acceptor molecules are distributed in individual organelles that usually have complex non-continuous shape. Consequently, background pixels arising from fluorophore-free regions of the cell are proximal to FRET-positive pixels, leading to systemic errors in the estimated FRET values. This study introduces a new FRET(TH) algorithm for FRET estimation by acceptor photobleaching that separates the FRET-positive pixels from the background by applying user-defined thresholds for pixel selection. The FRET(TH) algorithm was validated by analysis of interactions between fluorescently tagged proteins in the endoplasmic reticulum using acquired and simulated images. The novel algorithm showed superior performance to the regular FRET calculation algorithm in acquired images and in most simulations. The developed algorithm was incorporated into the FRETcalc plugin for ImageJ program that enables user-defined choices of thresholds for calculation of FRET by acceptor photobleaching. +Affiliation +Howard Hughes Medical Institute, Department of Immunobiology, Yale University School of Medicine, PO Box 208011, New Haven, CT 06520, USA. david.stepensky@yale.edu +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.bbrc.2007.05.180 +Language +eng +Pii +S0006-291X(07)01169-2 +Pmid +17555710 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.bbrc.2007.05.180 + +Barboriak:2005p14803 +Creation of DICOM--aware applications using ImageJ (article) +Author +Daniel P Barboriak and Anthony O Padua and Gerald E York and James R Macfall +Journal +J Digit Imaging +Year +2005 +Volume +18 +Number +2 +Pages +91--9 +Month +Jun +Keywords +Software, User-Computer Interface, Radiology Information Systems, Humans, Internet, Image Processing: Computer-Assisted +Abstract +The demand for image-processing software for radiology applications has been increasing, fueled by advancements in both image-acquisition and image-analysis techniques. The utility of existing image-processing software is often limited by cost, lack of flexibility, and/or specific hardware requirements. In particular, many existing packages cannot directly utilize images formatted using the specifications in part 10 of the DICOM standard ("DICOM images"). We show how image analyses can be performed directly on DICOM images by using ImageJ, a free, Java-based image-processing package (http://rsb.info.nih.gov/ij/). We demonstrate how plug-ins written in our laboratory can be used along with the ImageJ macro script language to create flexible, low-cost, multiplatform image-processing applications that can be directed by information contained in the DICOM image header. +Affiliation +Department of Radiology, Duke University Medical Center, PO Box 3808, Durham, NC, 27710, USA. barbo013@mc.duke.edu +Date-Added +2010-01-28 21:12:09 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s10278-004-1879-4 +Language +eng +Pmid +15827831 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s10278-004-1879-4 + +Mailly:2009p13793 +A 3D multi-modal and multi-dimensional digital brain model as a framework for data sharing (article) +Author +Philippe Mailly and Suzanne N Haber and Henk J Groenewegen and Jean-Michel Deniau +Journal +J Neurosci Methods +Year +2009 +Month +Dec +Abstract +Computer based three-dimensional reconstruction and co-registration of experimental data provide powerful tools for integration of observation derived from various technical approaches leading to better understanding of brain functions. Here we describe a method to build a 3D multi-modal and multi-dimensional model of brain structures providing framework for data sharing. All image processing, registration and 3D reconstruction were performed using open source software IMOD package software and ImageJ. The reconstruction procedure is based on series of AChE and Nissl stained sections aligned to blockface pictures. Integration of experimental data into the reference model is achieved by co-registration of Nissl sections of experimental brain cases by positioning landmarks on corresponding anatomical structures. To overcome the challenge of comparing for experimental sections with those of the reference model, adjustment of experimental model to the brain model was done section by section and limited to the structures of interest. For this adjustment we stress the use of cytoarchitectural criteria for accurate registration of anatomical structures and co-registration procedures. +Affiliation +Institut National de la Santé et de la Recherche Médicale UMRs 952, Centre National de Recherche Scientifique UMR 7224, Université Pierre et Marie Curie, 7-9 quai Saint Bernard, 75252, Paris Cedex 05, France. +Date-Added +2010-01-19 09:00:22 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.jneumeth.2009.12.014 +Language +ENG +Pii +S0165-0270(09)00678-5 +Pmid +20043949 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.jneumeth.2009.12.014 + +Swedlow:2009p13687 +Open source bioimage informatics for cell biology (article) +Author +Jason R Swedlow and Kevin W Eliceiri +Journal +Trends in Cell Biology +Year +2009 +Volume +19 +Number +11 +Pages +656--60 +Month +Nov +Keywords +Computational Biology, Cell Survival, Animals, Image Processing: Computer-Assisted, Cytological Techniques, Cell Biology +Abstract +Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery. +Affiliation +Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee, Scotland DD1 5EH, UK. jason@lifesci.dundee.ac.uk +Date-Added +2010-01-12 15:12:04 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.tcb.2009.08.007 +Language +eng +Pii +S0962-8924(09)00187-1 +Pmid +19833518 +Rating +0 +Local Files +~/Documents/Papers/Eliceiri Trends Cell Biol 2009.pdf +Remote URLs +http://dx.doi.org/10.1016/j.tcb.2009.08.007 + +Barry:2009p13825 +Morphological quantification of filamentous fungal development using membrane immobilization and automatic image analysis (article) +Author +David J Barry and Cecilia Chan and Gwilym A Williams +Journal +J Ind Microbiol Biotechnol +Year +2009 +Volume +36 +Number +6 +Pages +787--800 +Month +Jun +Keywords +Culture Techniques, Aspergillus oryzae, Kinetics, Spores: Fungal, Hyphae, Image Processing: Computer-Assisted, Membranes: Artificial +Abstract +Mycelial morphology is a critically important process property in industrial fermentations of filamentous micro-organisms, as particular phenotypes are associated with maximum productivity. However, the accurate quantification of complex morphologies still represents a significant challenge in elucidating this relationship. A system has been developed for high-resolution characterisation of filamentous fungal growth on a solid substrate, using membrane immobilization and fully-automatic plug-ins developed for the public domain, Java-based, image-processing software, ImageJ. The system has been used to quantify the microscopic development of Aspergillus oryzae on malt agar, by measuring spore projected area and circularity, the total length of a hyphal element, the number of tips per element, and the hyphal growth unit. Two different stages of growth are described, from the swelling of a population of conidiospores up to fully developed, branched hyphae 24 h after inoculation. Spore swelling expressed as an increase in mean equivalent spore diameter was found to be approximately linear with time. Widespread germination of spores was observed by 8 h after inoculation. From approximately 12 h, the number of tips was found to increase exponentially. The specific growth rate of a population of hyphae was calculated as approximately 0.24-0.27 h(-1). A wide variation in growth kinetics was found within the population. The robustness of the image-analysis system was verified by testing the effect of small variations in the input data. +Affiliation +School of Biological Sciences, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland. david.barry@dit.ie +Date-Added +2010-01-19 09:08:25 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s10295-009-0552-9 +Language +eng +Pmid +19277741 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s10295-009-0552-9 + +Hand:2009p13895 +Automated tracking of migrating cells in phase-contrast video microscopy sequences using image registration (article) +Author +A J Hand and T Sun and D C Barber and D R Hose and S MacNeil +Journal +Journal of microscopy +Year +2009 +Volume +234 +Number +1 +Pages +62--79 +Month +Apr +Keywords +Cells: Cultured, Microscopy: Video, Humans, Epithelial Cells, Microscopy: Phase-Contrast, Cell Movement +Abstract +Analysis of in vitro cell motility is a useful tool for assessing cellular response to a range of factors. However, the majority of cell-tracking systems available are designed primarily for use with fluorescently labelled images. In this paper, five commonly used tracking systems are examined for their performance compared with the use of a novel in-house cell-tracking system based on the principles of image registration and optical flow. Image registration is a tool commonly used in medical imaging to correct for the effects of patient motion during imaging procedures and works well on low-contrast images, such as those found in bright-field and phase-contrast microscopy. The five cell-tracking systems examined were Retrac, a manual tracking system used as the gold standard; CellTrack, a recently released freely downloadable software system that uses a combination of tracking methods; ImageJ, which is a freely available piece of software with a plug-in for automated tracking (MTrack2) and Imaris and Volocity, both commercially available automated tracking systems. All systems were used to track migration of human epithelial cells over ten frames of a phase-contrast time-lapse microscopy sequence. This showed that the in-house image-registration system was the most effective of those tested when tracking non-dividing epithelial cells in low-contrast images, with a successful tracking rate of 95%. The performance of the tracking systems was also evaluated by tracking fluorescently labelled epithelial cells imaged with both phase-contrast and confocal microscopy techniques. The results showed that using fluorescence microscopy instead of phase contrast does improve the tracking efficiency for each of the tested systems. For the in-house software, this improvement was relatively small (<5% difference in tracking success rate), whereas much greater improvements in performance were seen when using fluorescence microscopy with Volocity and ImageJ. +Affiliation +Kroto Research Institute, North Campus, University of Sheffield, Broad Lane, Sheffield, United Kingdom. +Date-Added +2010-01-19 09:10:21 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1365-2818.2009.03144.x +Language +eng +Pii +JMI3144 +Pmid +19335457 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1365-2818.2009.03144.x + +Hegyi:2009p13800 +Confocal laser-scanning capillaroscopy: a novel approach to the analysis of skin capillaries in vivo (article) +Author +J Hegyi and V Hegyi and G Messer and P Arenberger and T Ruzicka and C Berking +Journal +Skin Res Technol +Year +2009 +Volume +15 +Number +4 +Pages +476--81 +Month +Nov +Keywords +Adult, Microscopy: Confocal, Female, Humans, Middle Aged, Aged: 80 and over, Forearm, Male, Psoriasis, Reproducibility of Results, Microscopic Angioscopy, Young Adult, Sex Characteristics, Aged, Dermis +Abstract +BACKGROUND: New techniques for diagnostics and therapy in dermatology are becoming increasingly non-invasive, among which confocal laser-scanning microscopy (CLSM) is the most prevalent. It allows visualization of cellular structures of the skin up to a depth of 300 microm in vivo. Until now, most studies have been conducted on pathologically altered skin, mostly oncologic lesions. We now present a detailed analysis of capillaries located in the upper dermal papillae. METHODS: Multiple measurements were performed on the dorsal and ventral surface of the right forearm of 30 healthy volunteers (22-88 years) under standard conditions (room temperature, body position, time of day). Images were obtained with the Vivascope 1500 (Lucid) under standard settings and analyzed using the freeware ImageJ with a customwritten macro plugin. The following parameters of the capillaries in vivo were measured: area, perimeter, circularity and maximum diameter. RESULTS: Statistical analysis showed that all four parameters were constant within a narrow range, regardless of the body site, sex and age. In this physiological study, we can clearly demonstrate that by confocal laser-scanning capillaroscopy (CLSC), it is possible to visualize and measure skin capillaries at the extremities in a reproducible manner. CONCLUSION: This new approach offers a considerable advantage compared with nailfold capillaroscopy, which can only be performed at the proximal nail segment, and over histological analysis, which can be hampered by fixation artifacts resulting in altered size and shape of the vessels to be analyzed. CLSC could allow for precise analysis of in vivo skin vasculature in systemic and proliferative diseases of the skin. +Affiliation +Department of Dermatology, Ludwig-Maximilian University, Munich, Germany. +Date-Added +2010-01-19 09:04:03 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1111/j.1600-0846.2009.00393.x +Language +eng +Pii +SRT393 +Pmid +19832961 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1600-0846.2009.00393.x + +Sheffield:2007p14899 +ImageJ, a useful tool for biological image processing and analysis (article) +Author +Joel B Sheffield +Journal +Microsc Microanal +Year +2007 +Volume +13 +Pages +200--201 +Month +Jan +Affiliation +Temple Univ, Dept Biol, Philadelphia, PA 19122 USA +Date-Added +2010-01-29 10:43:46 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1017/S1431927607076611 +Language +English +Pmid +000258691300100 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1017/S1431927607076611 + +Doube:2006p14914 +ImageJ and analysis of correlated confocal and BSE-SEM imaging (article) +Author +M Doube +Journal +Scanning +Year +2006 +Volume +28 +Number +2 +Pages +93--94 +Month +Jan +Affiliation +QMUL, Biophys OGD, Inst Dent, London, England +Date-Added +2010-01-29 10:43:46 -0500 +Date-Modified +2012-06-07 09:49:15 -0400 +Doi +10.1111/j.1469-7580.2012.01514.x +Language +English +Pmid +000237012500048 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1111/j.1469-7580.2012.01514.x + +Scorcioni:2008p14992 +Point analysis in Java applied to histological images of the perforant pathway: A user's account (editorialmaterial) +Keywords +Hippocampus, Projection, Entorhinal Cortex, Image Analysis +Abstract +The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ. +Affiliation +George Mason Univ, Krasnow Inst Adv Study, Fairfax, VA 22030 USA +Author +Ruggero Scorcioni and Susan N Wright and JPatrick Card and Giorgio A Ascoli and German Barrionuevo +Date-Added +2010-01-29 10:50:06 -0500 +Date-Modified +2011-07-06 15:22:18 -0400 +Doi +10.1007/s12021-008-9011-4 +Journal +Neuroinformatics +Language +English +Month +Jan +Number +1 +Pages +63--67 +Pmid +000256328000007 +Rating +0 +Volume +6 +Year +2008 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s12021-008-9011-4 + +Kim:2006p13953 +Automated nuclear segmentation in the determination of the Ki-67 labeling index in meningiomas (article) +Author +Y J Kim and B F M Romeike and J Uszkoreit and W Feiden +Journal +Clin Neuropathol +Year +2006 +Volume +25 +Number +2 +Pages +67--73 +Month +Jan +Keywords +Humans, Tumor Markers: Biological, Immunohistochemistry, Meningioma, Meningeal Neoplasms, Image Processing: Computer-Assisted, Cell Nucleus, Reproducibility of Results, Ki-67 Antigen, Sensitivity and Specificity +Abstract +OBJECTIVE: Assessing the Ki-67 labeling index (LI) is laborious and time consuming. Therefore, an automated computer-based method was developed, which is able to identify and analyze immunolabeled and hematoxylin-stained nuclei in digital images of routine immunohistochemical slides. MATERIAL AND METHODS: The method is based on a plugin for the public domain image analysis software ImageJ, which runs on every operating system (free download at http://rsb.info.nih.gov/ij/). Percentage of Ki-67 immunostained nuclei were determined in 5 high power fields (x40) of immunostained slides (DAB detection technique, hematoxylin counterstain) of 20 Grade I, 20 Grade II, and 10 Grade III meningiomas conventionally by two independent investigators and automatically, respectively. The time effort was measured for each counting procedure. RESULTS: Enumerating conventionally or automatically did not reveal any significant differences in the mean labeling indices. Ki-67 LIs discriminated sufficiently between meningiomas of Grade I (median 1.7% Investigator 1 and 1.5% Investigator 2 vs. 1.5% automatically), Grade II (7.6%, 8% vs. 7.3%), and Grade III meningiomas (22%, 21% vs. 22%). The computer-based results correlated very closely with those obtained by manual counting (correlation coefficient = 0.98). The mean time effort for counting procedure per image was 374 s (130 s-435 s) for the conventional and 11 s (7 s-12 s) for the automated method. CONCLUSIONS: The described method can reliably assess the Ki-67 LI much faster than conventional enumerating. The computerized method has the advantages of objectivity, accuracy, repeatability, and ease of use. There is no request for special stains nor special image acquiring systems. The plugin can be downloaded at the "Morphometrie" section of http://www.uniklinikum-saarland.de/neuropathologie. +Affiliation +Institute of Neuropathology, University of the Saarland, School of Medicine, Homburg-Saar, Germany. yoo.jin.kim@uniklinikum-saarland.de +Date-Added +2010-01-19 09:12:56 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Language +eng +Pmid +16550739 +Rating +0 +Local Files +Remote URLs + +Hegge:2009p15143 +Automated classification of Plasmodium sporozoite movement patterns reveals a shift towards productive motility during salivary gland infection (article) +Author +Stephan Hegge and Mikhail Kudryashev and Ashley Smith and Friedrich Frischknecht +Journal +Biotechnol J +Year +2009 +Volume +4 +Number +6 +Pages +903--13 +Month +Jun +Keywords +Cell Movement, Age Factors, Plasmodium berghei, Green Fluorescent Proteins, Image Processing: Computer-Assisted, Anopheles, Microscopy: Fluorescence, Sporozoites, Salivary Glands, Pattern Recognition: Automated, Animals, Temperature, User-Computer Interface +Abstract +The invasive stages of malaria and other apicomplexan parasites use a unique motility machinery based on actin, myosin and a number of parasite-specific proteins to invade host cells and tissues. The crucial importance of this motility machinery at several stages of the life cycle of these parasites makes the individual components potential drug targets. The different stages of the malaria parasite exhibit strikingly diverse movement patterns, likely reflecting the varied needs to achieve successful invasion. Here, we describe a Tool for Automated Sporozoite Tracking (ToAST) that allows the rapid simultaneous analysis of several hundred motile Plasmodium sporozoites, the stage of the malaria parasite transmitted by the mosquito. ToAST reliably categorizes different modes of sporozoite movement and can be used for both tracking changes in movement patterns and comparing overall movement parameters, such as average speed or the persistence of sporozoites undergoing a certain type of movement. This allows the comparison of potentially small differences between distinct parasite populations and will enable screening of drug libraries to find inhibitors of sporozoite motility. Using ToAST, we find that isolated sporozoites change their movement patterns towards productive motility during the first week after infection of mosquito salivary glands. +Affiliation +Department of Parasitology, Hygiene Institute, University of Heidelberg Medical School, Heidelberg, Germany. +Date-Added +2010-01-29 11:05:46 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/biot.200900007 +Language +eng +Pmid +19455538 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/biot.200900007 + +Goodall:2009p14015 +3-Dimensional modelling of chick embryo eye development and growth using high resolution magnetic resonance imaging (article) +Author +Nicola Goodall and Lilian Kisiswa and Ankush Prashar and Stuart Faulkner and Paweł Tokarczuk and Krish Singh and Jonathan T Erichsen and Jez Guggenheim and Willi Halfter and Michael A Wride +Journal +Exp Eye Res +Year +2009 +Volume +89 +Number +4 +Pages +511--21 +Month +Oct +Abstract +Magnetic resonance imaging (MRI) is a powerful tool for generating 3-dimensional structural and functional image data. MRI has already proven valuable in creating atlases of mouse and quail development. Here, we have exploited high resolution MRI to determine the parameters necessary to acquire images of the chick embryo eye. Using a 9.4 Tesla (400 MHz) high field ultra-shielded and refrigerated magnet (Bruker), MRI was carried out on paraformaldehyde-fixed chick embryos or heads at E4, E6, E8, and E10. Image data were processed using established and custom packages (MRICro, ImageJ, ParaVision, Bruker and mri3dX). Voxel dimensions ranged from 62.5 microm to 117.2 microm. We subsequently used the images obtained from the MRI data in order to make precise measurements of chick embryo eye surface area, volume and axial length from E4 to E10. MRI was validated for accurate sizing of ocular tissue features by direct comparison with previously published literature. Furthermore, we demonstrate the utility of high resolution MRI for making accurate measurements of morphological changes due to experimental manipulation of chick eye development, thereby facilitating a better understanding of the effects on chick embryo eye development and growth of such manipulations. Chondroitin sulphate or heparin were microinjected into the vitreous cavity of the right eyes of each of 3 embryos at E5. At E10, embryos were fixed and various eye parameters (volume, surface area, axial length and equatorial diameter) were determined using MRI and normalised with respect to the un-injected left eyes. Statistically significant alterations in eye volume (p < 0.05; increases with chondroitin sulphate and decreases with heparin) and changes in vitreous homogeneity were observed in embryos following microinjection of glycosaminoglycans. Furthermore, in the heparin-injected eyes, significant disturbances at the vitreo-retinal boundary were observed as well as retinal folding and detachment confirming histological observations. These data reveal the utility and superiority of MRI for producing images enabling quantification of experimentally induced changes in eye volume and structure. The results indicate that MRI is an important tool that could become a routine approach for rapid and sensitive phenotypic analysis of normal chick ocular development and morphology as well as potentially the effects of surgical or genetic manipulations of chick embryo eyes in live embryos in ovo. +Affiliation +Visual Neuroscience and Molecular Biology Research Group, School of Optometry and Vision Sciences, Cardiff University, Maindy Road, Cardiff, Wales, CF24 4LU, UK. nicola.goodall@hotmail.co.uk +Date-Added +2010-01-19 09:20:22 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1016/j.exer.2009.05.014 +Language +eng +Pii +S0014-4835(09)00164-X +Pmid +19540232 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1016/j.exer.2009.05.014 + +Lessman:2007p13901 +Computer-aided meiotic maturation assay (CAMMA) of zebrafish (Danio rerio) oocytes in vitro (article) +Author +Charles A Lessman and Ravikanth Nathani and Rafique Uddin and Jamie Walker and Jianxiong Liu +Journal +Mol Reprod Dev +Year +2007 +Volume +74 +Number +1 +Pages +97--107 +Month +Jan +Keywords +Oocytes, Tissue Array Analysis, Meiosis, Zebrafish, Image Processing: Computer-Assisted, Animals, Female, Cytogenetic Analysis +Abstract +We have developed a new technique called Computer-Aided Meiotic Maturation Assay (CAMMA) for imaging large arrays of zebrafish oocytes and automatically collecting image files at regular intervals during meiotic maturation. This novel method uses a transparency scanner interfaced to a computer with macro programming that automatically scans and archives the image files. Images are stacked and analyzed with ImageJ to quantify changes in optical density characteristic of zebrafish oocyte maturation. Major advantages of CAMMA include (1) ability to image very large arrays of oocytes and follow individual cells over time, (2) simultaneously image many treatment groups, (3) digitized images may be stacked, animated, and analyzed in programs such as ImageJ, NIH-Image, or ScionImage, and (4) CAMMA system is inexpensive, costing less than most microscopes used in traditional assays. We have used CAMMA to determine the dose response and time course of oocyte maturation induced by 17alpha-hydroxyprogesterone (HP). Maximal decrease in optical density occurs around 5 hr after 0.1 micro g/ml HP (28.5 degrees C), approximately 3 hr after germinal vesicle migration (GVM) and dissolution (GVD). In addition to changes in optical density, GVD is accompanied by streaming of ooplasm to the animal pole to form a blastodisc. These dynamic changes are readily visualized by animating image stacks from CAMMA; thus, CAMMA provides a valuable source of time-lapse movies for those studying zebrafish oocyte maturation. The oocyte clearing documented by CAMMA is correlated to changes in size distribution of major yolk proteins upon SDS-PAGE, and, this in turn, is related to increased cyclin B(1) protein. +Affiliation +The University of Memphis, Department of Biology, Memphis, TN 38152-3540, USA. Clessman@memphis.edu +Date-Added +2010-01-19 09:10:50 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1002/mrd.20530 +Language +eng +Pmid +16998847 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1002/mrd.20530 + +MeyerDosSantos:2010p13798 +Using ImageJ for the quantitative analysis of flow-based adhesion assays in real-time under physiologic flow conditions (article) +Author +Sascha Meyer Dos Santos and Ute Klinkhardt and Reinhard Schneppenheim and Sebastian Harder +Journal +Platelets +Year +2010 +Volume +21 +Number +1 +Pages +60--6 +Month +Feb +Abstract +This article intends to close the gap between the abundance of regular articles focusing on adhesive mechanisms of cells in a flow field and purely technical reports confined to the description of newly developed algorithms, not yet ready to be used by users without programming skills. A simple and robust method is presented for analysing raw videomicroscopic data of flow-based adhesion assays using the freely available public domain software ImageJ. We describe in detail the image processing routines used to rapidly and reliably evaluate the number of adherent and translocating platelets in videomicroscopic recordings. The depicted procedures were exemplified by analysing platelet interaction with immobilized von Willebrand factor and fibrinogen in flowing blood under physiological wall shear rates. Neutralizing GPIbalpha function reduced shear-dependent platelet translocation on von Willebrand factor and abolished firm platelet adhesion. Abciximab, Tirofiban and Eptifibatide completely inhibited GPIIb/IIIa-dependent stable platelet deposition on fibrinogen. The presented method to analyse videomicroscopic recordings from flow-based adhesion assays offers the advantage of providing a simple and reliable way to quantify flow-based adhesion assays, which is completely based on ImageJ and can easily be applied to study adhesion mechanisms of cells in non-fluorescent modes without the need to deviate from the presented protocol. +Affiliation +Department of Clinical Pharmacology, Klinikum, J.W.Goethe-Universität Frankfurt/Main, Germany. +Date-Added +2010-01-19 08:59:30 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.3109/09537100903410609 +Language +eng +Pmid +20001786 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.3109/09537100903410609 + +Shprung:2009p13838 +A novel method for analyzing mitochondrial movement: inhibition by paclitaxel in a pheochromocytoma cell model (article) +Author +Tal Shprung and Illana Gozes +Journal +J Mol Neurosci +Year +2009 +Volume +37 +Number +3 +Pages +254--62 +Month +Mar +Keywords +Paclitaxel, Fluorescent Dyes, Pheochromocytoma, Rats, PC12 Cells, Cell Line: Tumor, Mitochondria, Antineoplastic Agents: Phytogenic, Adrenal Gland Neoplasms, Animals +Abstract +A method was developed to assess mitochondrial movement in the living cell that is dependent, in part, on microtubule and/or associating protein interactions. The leader sequence from cytochrome-c was used to drive DsRed2 fluorescent proteins to accumulate in the mitochondria, thus enabling to follow mitochondrial (cytochrome-c's) movement. For calculating the percentage of mitochondrial movement, an image-processing program was used (ImageJ). Paclitaxel, an antitumor agent, is a potent microtubule-stabilizing agent that increases the stability of tubulin polymers, inhibiting mitosis and mitochondrial activity in dividing cells. Here, we tested whether paclitaxel inhibits mitochondrial movement in pheochromocytoma cells (a neuronal model, when tested in a differentiated state). While a 2-day exposure to paclitaxel resulted in cellular toxicity (measured as inhibition of mitochondrial activity), 2-3 h exposure to paclitaxel were sufficient to inhibit mitochondrial movement as assessed in 10-20-s imaging sessions in living cells. Mitotracker deep-red staining validated the staining obtained with DsRed2-cytochrome-c and identified intact mitochondria. Results showed a significant paclitaxel dose-dependent inhibition of mitochondrial movement. This new method should enable further assessment of microtubule-interacting drugs and other cytoskeletal components for their potential influence of mitochondrial movement as a test for activity and side effects. +Affiliation +Department of Human Molecular Genetics and Biochemistry, Sackler Medical School, Tel Aviv University, Tel Aviv, 69978, Israel. +Date-Added +2010-01-19 09:09:35 -0500 +Date-Modified +2011-07-06 15:13:34 -0400 +Doi +10.1007/s12031-008-9129-8 +Language +eng +Pmid +18636346 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1007/s12031-008-9129-8 + +Crawford:2009p15126 +An ImageJ plugin for the rapid morphological characterization of separated particles and an initial application to placer gold analysis (article) +Author +Evan C Crawford and James K Mortensen +Journal +Computers {\&} Geosciences +Year +2009 +Volume +35 +Pages +347 +Month +Feb +Abstract +Not Available +Date-Added +2010-01-29 10:57:19 -0500 +Date-Modified +2012-06-07 09:41:07 -0400 +Doi +10.1016/j.cageo.2007.11.012 +Pmid +2009CG.....35..347C +Rating +0 +Local Files +Remote URLs +http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009CG.....35..347C&link_type=EJOURNAL +http://dx.doi.org/10.1016/j.cageo.2007.11.012 + +Preibisch:2009p13909 +Globally optimal stitching of tiled 3D microscopic image acquisitions (article) +Author +Stephan Preibisch and Stephan Saalfeld and Pavel Tomancak +Journal +Bioinformatics +Year +2009 +Volume +25 +Number +11 +Pages +1463--5 +Month +Jun +Keywords +Microscopy: Confocal, Larva, Animals, Drosophila, Imaging: Three-Dimensional +Abstract +MOTIVATION: Modern anatomical and developmental studies often require high-resolution imaging of large specimens in three dimensions (3D). Confocal microscopy produces high-resolution 3D images, but is limited by a relatively small field of view compared with the size of large biological specimens. Therefore, motorized stages that move the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow direct reconstruction (Stitching) of the whole image from individual image stacks. RESULTS: To optimally stitch a large collection of 3D confocal images, we developed a method that, based on the Fourier Shift Theorem, computes all possible translations between pairs of 3D images, yielding the best overlap in terms of the cross-correlation measure and subsequently finds the globally optimal configuration of the whole group of 3D images. This method avoids the propagation of errors by consecutive registration steps. Additionally, to compensate the brightness differences between tiles, we apply a smooth, non-linear intensity transition between the overlapping images. Our stitching approach is fast, works on 2D and 3D images, and for small image sets does not require prior knowledge about the tile configuration. AVAILABILITY: The implementation of this method is available as an ImageJ plugin distributed as a part of the Fiji project (Fiji is just ImageJ: http://fiji.sc/). +Affiliation +Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. +Date-Added +2010-01-19 09:11:15 -0500 +Date-Modified +2012-06-06 23:04:48 -0400 +Doi +10.1093/bioinformatics/btp184 +Language +eng +Pii +btp184 +Pmid +19346324 +Rating +0 +Local Files +Remote URLs +http://dx.doi.org/10.1093/bioinformatics/btp184 diff --git a/plain/09-about.txt b/plain/09-about.txt new file mode 100644 index 0000000..6542de9 --- /dev/null +++ b/plain/09-about.txt @@ -0,0 +1,131 @@ + +Colophonsec:About-this-Guide + +The initial contents of this guide have been retrieved in 2009 from +the http://imagej.nih.gov/ij/ImageJ website using http://www.mbayer.de/html2text/html2text. +Since then, it has been complemented and updated using informations +posted on the http://imagej.nih.gov/ij/list.htmlImageJ mailing list, +http://imagejdocu.tudor.lu/doku.php?id=startImageJ Documentation Portal, +http://fiji.sc/wiki/index.php/FijiFiji, http://imagej.nih.gov/ij/ImageJ, +and http://developer.imagej.net/ImageJDev websites and Tony +Collins http://www.macbiophotonics.ca/imagej/ImageJ for Microscopy +manual. Nevertheless, because there has never been accompanying documentation +for some of the 350+ described commands, several sections have been +written from scratch based on the relevant http://imagej.nih.gov/ij/developer/source/index.htmlImageJ source code +and authors own experience. Legacy nomenclature that became obsolete +with version has been intentionally omitted. + +The guide was typeset with Live2012 on Mac OS10.6.8. +All illustrations were created with ImageJ/Fiji, loaded with G. Landini's +http://fiji.sc/wiki/index.php/IJ_RobotIJ Robot and J. Schindelin's +http://fiji.sc/wiki/index.php/Tutorial_MakerTutorial Maker +plugins. Screenshots were produced by the screencapture +shell utility controlled by the following IJ macro: +lstlisting[otherkeywords==,showstringspaces=false,tabsize=4] + exec("screencapture -ciWo > /dev/null 2>&1 &"); run("System Clipboard"); + setLineWidth(1); setForegroundColor(111, 121, 132); + drawRect(0, 0, getWidth, getHeight); +lstlisting + + +The HTML version was produced with http://elyxer.nongnu.org/eLyXer 1.2 +and formatted using CSS code from Alex Fernndez and Michael Hneburg; +JavaScript code from Ciarn O'Kelly, Stuart Langridge and Tiago Ferreira. +It uses http://alexgorbatchev.com/SyntaxHighlighter/SyntaxHighlighter +and icons from the http://tango.freedesktop.org/Tango_Desktop_ProjectTango Desktop Project. + + +Getting Involvedsub:Getting-Involved + +Your help is needed to improve ImageJ. Even if you are not a programmer, +your participation is important: +itemize +Are you a skilled ImageJ user? + +You might want to help out with the documentation effort: Write a +FAQ, How-To, Tutorial or http://imagejdocu.tudor.lu/doku.php?id=video:startVideo Tutorial +on the http://imagejdocu.tudor.lu/doku.php?id=howto:general:how_to_use_this_documenation_wikiImageJ Documentation Portal; +Help us updating the ImageJ User Guide; Share the add-ons you may +have created with the community; Subscribe the http://imagej.nih.gov/ij/list.htmlmailing list +and help answering the questions raised by other users. +Are you know knowledgeable in image processing? + +Please join the http://imagej.nih.gov/ij/list.htmlmailing list +and participate in the discussions. You could also write a Tutorial +on the http://imagejdocu.tudor.lu/doku.php?id=howto:general:how_to_use_this_documenation_wikiImageJ Documentation Portal. +Do you have a strong scientific background? + +Frequently, the most demanding tasks in scientific image processing +relate to experimental design. Even if you do not have special expertise +in image processing, by participating on the http://imagej.nih.gov/ij/list.htmlmailing list +discussions, your experience will be valuable to others. +Do you want ImageJ to improve? + +You can report bugs or request new features using the http://imagej.nih.gov/ij/list.htmlmailing list. +Do you have experience in graphic/web design? + +If you are able to to improve the look and feel of the guide we welcome +your skills. +itemize + +The ImageJ Iconsec:About-the-Cover + +The Hartnack@Hartnack IJ icon,IJ iconHartnack +microscope (ca. 1870's) depicted on the front page inspired +the http://imagej.nih.gov/ij/docs/install/osx.htmliconImageJ icon for Mac OS X. +It is based on a http://www.arsmachina.com/s-hart1209.htmphotograph +by http://www.tomgrill.com/Tom Grill at http://www.arsmachina.com/arsmachina.com. + +Edmund Hartnack (1826-1891) was a renown microscope manufacturer +that pioneered the use of correction collars in water-immersion lenses +and the adoption of the substage condenser(Merico, G. Microscopy in Camillo Golgi's times. J Hist Neurosci, +(2003) 8(2):113-20). The precision and robustness of Hartnack optics played a pivotal +role in the groundbreaking research by the Nobel laureates Robert +Koch(Brock, TD. Robert Koch, A life in medicine and bacteriology. +ASM, 1999), Camillo Golgi(Brenni P. Gli strumenti di fisica dell'Istituto Tecnico Toscano - +Ottica. IMSS, 1995 ) and Santiago Ramn y Cajal(DeFelipe Jones. Santiago Ramn y Cajal and methods in neurohistology. +Trends Neurosci, (1992) 15(7):237-46). + + + +[1]Revision Historyrevisionhistory + + +Document Revision Historysec:Document-Revision-History + +center +tabular>p0.19>p0.72 + +1cDate & 1cNotesSeptember/October 2012 & Reviewed by Michael SchmidJuly 2012 & Updated for v1.46r + +Reviewed by Barry DeZoniaJune 2012 & Updated for v1.46p + +Second major revision with new sections on overlays, 3D volumes, sub-pixel +selections, curve fitting and interface customizations + +Improvements in layout and browsabilitySeptember 2011 & Updated for v1.45 + +Deeply revised edition with several new sections in Parts I-IV + +Available as printable booklets + +Redesigned HTML version January 2011 & Updated for v1.44 + +New sections on advanced ImageJ usage, Fiji scripting, command line +usage and interoperability with other software packagesMay 2010 & First HTML versionApril 2010 & First edition: v1.43tabular +center + + + + + +Acknowledgments + +We are extremely grateful to Alex Fernndez for his wonderful http://elyxer.nongnu.org/eLyXer, +Alex Gorbatchev for http://alexgorbatchev.com/SyntaxHighlighter/SyntaxHighlighter, +Johannes Schindelin for assistance with the http://fiji.sc/guide.gitGit repository, +Norbert Vischer for critical corrections and Michael Schmid and Barry +DeZonia for thorough revisions. We are also thankful to all of those +who submitted criticisms, suggestions and encouragement to update +this edition. But above all, our thanks go to the extraordinary ImageJ +community for its dedication to the project.