Dicom Anonymizer

This appears to be a locally-run DICOM anonymizer and is internally consistent, but before using it on real patient data: 1) Review the full scripts/main.py (truncated portions) to confirm there are no hidden network calls, telemetry, or code paths that write PHI elsewhere. 2) Verify the hashing/pseudonymization approach (is a salt used? how are pseudonym mappings stored?) so hashes cannot be trivially correlated across datasets or leaked. 3) Ensure audit logs do not leak raw PHI (store them securely and limit access). 4) Test on synthetic data to confirm pixel data and burned-in text (if any) are handled as you expect — many anonymizers do not OCR burned-in patient identifiers. 5) Install pydicom and other dependencies from trusted sources (official PyPI) and run in an isolated environment until you're confident. If you want, I can scan the remaining/truncated parts of scripts/main.py for specific concerns (network calls, subprocess usage, writing to unexpected locations) — provide the full file and I'll review it.