The rules used for redacting DICOM images are based on pydicom deid's rules which in turn are based on CTP's rules.
These rules can be created manually or by using dcmaudit.py (or even
dicom_ocr.py). Save the rectangles to a database and then use the utility
dbrects_to_deid_rules.py to create rules.
Rules specify a set of DICOM metadata tags, all of which must match, and then a set of rectangles to be redacted.
Rules can also be used to derive a set of rectangles from Ultrasound images if they contain the DICOM tag SequenceOfUltrasoundRegions.
Note that rule-based redaction has to be applied to every frame and every overlay in a file because the rules have no way to specify individual frames.
This example redacts XA images of size 1024x1024 if they have two
private tags which are known to be used by Ziehm Vision machines.
This requires the latest verision of pydicom/deid that has support
for private tags. Note how the contains rule can be a regular expression.
LABEL Ziehm X-Rays 1024
contains Modality XA
+ contains 0x00190010 ZIEHM_1.0
+ contains 0x00191201 Fluoro|LowDose|Snapshot|HiQ|LPK|HLC
+ equals Rows 1024
+ equals Columns 1024
coordinates 0,0,196,148
coordinates 0,940,189,1006
coordinates 706,0,1023,66
This example will return rectangles if present in SequenceOfUltrasoundRegions tag.
Note that it uses keepcoordinates so that the deid library function knows to
invert them before returning rectangles to be redacted.
Note one difference from the pydicom/deid rules is that there is no need
for an inverse mask to be specified using coordinates all when using Ultrasound
regions because all coordinates specified using keepcoordinates will be
inverted automatically.
LABEL Clean Areas Outside Ultrasound Regions
present SequenceOfUltrasoundRegions
keepcoordinates from:SequenceOfUltrasoundRegions
- CTP metadata anonymiser
- CTP pixel anonymiser
- pydicom deid