Dcm-anon: DICOM anonymizer with a verbatim-cited GDPR/HIPAA compliance manifest
Dcm-anon is an open-source DICOM anonymizer designed to ensure compliance with GDPR and HIPAA regulations. It provides a machine-verifiable compliance manifest that details the de-identification process, making it suitable for research data sharing. The tool addresses legal traceability gaps in cross-hospital data preparation by implementing a comprehensive audit trail and independent output verification.
- ▪Dcm-anon implements the DICOM PS3.15 Basic Application Level Confidentiality Profile, ensuring UID consistency across files.
- ▪The tool emits a tamper-evident JSON and Markdown artifact that maps each action to specific regulatory clauses.
- ▪It includes features like an audit log, independent output verification, and the ability to handle nested PHI in sequence items.
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dcm-anon OSS DICOM anonymizer with a verbatim-cited, machine-verifiable compliance manifest — for research-data sharing under GDPR Art. 35 DPIA and HIPAA Safe Harbor. Why this exists GDPR Art. 35 makes a DPIA mandatory for large-scale processing of health data, and best practice — endorsed by the EDPS, the EDPB pseudonymisation guidelines (01/2025), and HHS OCR — is to de-identify at the source site before moving research data off-prem. Doing that defensibly means: A traceable mapping from each tag you removed to the specific clause that obliges you to remove it. An independent second opinion that the output does not still contain PHI. An audit trail that a regulator, IRB, or ethics committee can verify without your help. Most DICOM anonymizers do step 1 implicitly and skip steps 2 and 3.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.