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Tool to anonymize a dataset of medical images.
Key Investigators
  - Hina Shah (UNC Chapel Hill)
 
  - Juan Carolos Prieto (UNC Chapel Hill)
 
  - Fryderyk Kögl (BWH, TUM)
 
Project Description
The very first step to make any medical data available to research community is it’s anonymization. While there are ways to anonymize a single DICOM/non-dicom image in 3D Slicer, there’s no module to do this for a full dataset.
The proposed tool will:
  - Anonymize a dataset of images by deleting any identifiable metadata information
 
  - Have options to rename the files using either UUID or custom name.
 
  - Create a crosswalk to get the correspondence between anonymized and original files
 
  - Work as a standalone app or a slicer extension
 
Objective
  - Objective A. Write tests
 
  - Objective B. Push the extension to Slicer Extension Index
 
  - Objective C. Find out what other features/enhancements can be added to this extension
 
Approach and Plan
  - Identify existing anonymization pipelines for DICOM
 
  - Modify code to make the extension be available as an extension (not a standalone app), and push it to Slicer Extension Index
 
  - Within the community try to find out what other features would be useful to add to the extension.
 
Progress and Next Steps
  - Worked on a couple of issues for the extension
 
  - The extension has been pushed to the Slicer Extension Index.
 
  - Had a productive discussion with a few folks in the community to understand what are the existing tools/conformances for DICOM anonymization - this needs more introspection and research on our part, and deciding how we want to proceed - especially for the dental research data sharing purposes.
 
  - Will add a few suggested features, for example: letting users chose which metadata to anonymize.
 
Illustrations

Background and References
  - Source code in Github repository