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Source  : 5bbf9f0
Branch  : main
Author  : davecash75 <[email protected]>
Time    : 2024-09-23 09:29:01 +0000
Message : Merge pull request #6 from HealthBioscienceIDEAS/lg-patch

Update imaging-data-structure-and-formats.Rmd
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actions-user committed Sep 23, 2024
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5 changes: 3 additions & 2 deletions imaging-data-structure-and-formats.md
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Expand Up @@ -44,7 +44,7 @@ example [dcm2niix](https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPag

:::::::::::::::::::::: discussion
If you are interested in trying out converting DICOM data to Nifti, we have some
sample DICOM data for you. Please see the [bonus exercise](#) at the end of this lesson
sample DICOM data for you. Please see the [bonus exercise](#bonus_dicom) at the end of this lesson
if you would like to give this a go.
::::::::::::::::::::::

Expand Down Expand Up @@ -779,6 +779,7 @@ brain lesions – white matter hyperintensities – are more clearly visible
:::::::::::::::::::::::::::::::::
:::::::::::::::::::::::::::::::::
<a id="bonus_dicom"></a>
::::::::::::::::::::: challenge
### BONUS EXERCISE: DICOM to NIfTI
As discussed earlier, if you have received medical imaging data from a hosptial it is likely in
Expand All @@ -798,7 +799,7 @@ mkdir Nifti
```
1. How do we know how to use this command?
2. Construct a command to convert the images and put them in the directory `mkdir data/ImageDataVisualization/DICOM/Subject01/Nifti`
2. Construct a command to convert the images and put them in the directory `data/ImageDataVisualization/DICOM/Subject01/Nifti`
3. Figure out what option to use to store a compressed gzipped-version of the NIfTI file.
4. Try out some different options to make the name easier to manage.
5. Look at the converted NIfTI images in `fsleyes`. What modalities are they?
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32 changes: 16 additions & 16 deletions md5sum.txt
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