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Remediation

dicomqc reports metadata problems without changing the files. Fix the reported problems with your pseudonymization or anonymization tool, then audit the output again.

Copy source DICOM files, de-identify them, audit with dicomqc, and fix problems before sharing

Update the de-identification settings, generate a new copy, and rerun dicomqc to check that the problems are fixed.

Safe working pattern​

Never modify the only copy of a DICOM dataset. Work on a copy or on the output of a controlled pseudonymization/de-identification pipeline.

cp -a raw_study pseudonymized_study

Run the audit:

dicomqc scan pseudonymized_study/ --json report.json --csv findings.csv --multiqc

Apply fixes with your chosen tool, then rerun the audit:

dicomqc scan pseudonymized_study/ --json report-after-fix.json --csv findings-after-fix.csv --multiqc

DCMTK dcmodify​

DCMTK is a common command-line toolkit for DICOM operations. Its dcmodify command can remove or replace metadata tags.

Example: remove direct PHI fields from all .dcm files in a working copy:

find pseudonymized_study -name '*.dcm' -print0 \
  | xargs -0 dcmodify \
      -e PatientBirthDate \
      -e PatientAddress \
      -e PatientTelephoneNumbers \
      -e InstitutionAddress \
      -e ReferringPhysicianName \
      -e OperatorsName \
      -e AccessionNumber

Example: replace pseudonym fields:

dcmodify \
  -i PatientName=SUBJ001 \
  -i PatientID=SUBJ001 \
  pseudonymized_study/image.dcm

Private tags require project-specific judgment. Removing all private tags may be appropriate for some releases but may also remove scanner- or research-relevant metadata.

dcmodify -e "(0029,0010)" pseudonymized_study/image.dcm

Use your installed DCMTK version's documented options for broad private-tag removal, or enumerate the private tags that your release policy says must be removed. Check the exact dcmodify syntax before using these commands in production.

Orthanc​

Orthanc can anonymize DICOM instances through its REST API and configuration. This is useful when DICOM ingestion and de-identification already happen inside an Orthanc workflow.

Recommended pattern:

  1. Import or route data into Orthanc.
  2. Use Orthanc anonymization to create a derived dataset.
  3. Export the derived dataset.
  4. Run dicomqc on the exported result.

dicomqc should audit the exported candidate release, not the original Orthanc store.

XNAT and site pipelines​

For XNAT-based workflows, apply XNAT anonymization scripts or containerized pipeline steps first, then run dicomqc on the resulting DICOM export.

You can audit exported files this way regardless of the platform used to manage them.

Custom pydicom scripts​

You can also edit metadata with a custom pydicom script. Run the script as a separate step, then use dicomqc to check its output and save the results.

Future remediation plans​

A future release may write recommended fixes in a format that other tools can read:

required_changes:
  - tag: PatientBirthDate
    action: remove
  - tag: PatientName
    action: replace_with_pseudonym
  - tag: PrivateTags
    action: review_or_remove

The plan would still be applied by external tools. dicomqc remains read-only.