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Anonymization of a batch of DICOM files

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

  1. Objective A. Write tests
  2. Objective B. Push the extension to Slicer Extension Index
  3. Objective C. Find out what other features/enhancements can be added to this extension

Approach and Plan

  1. Identify existing anonymization pipelines for DICOM
  2. Modify code to make the extension be available as an extension (not a standalone app), and push it to Slicer Extension Index
  3. Within the community try to find out what other features would be useful to add to the extension.

Progress and Next Steps

  1. Worked on a couple of issues for the extension
  2. The extension has been pushed to the Slicer Extension Index.
  3. 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.
  4. Will add a few suggested features, for example: letting users chose which metadata to anonymize.

Illustrations

image

Background and References

  1. Source code in Github repository