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dicom-series-preflight

Check one DICOM medical imaging series before conversion or AI inference by inspecting headers only. Produce a JSON report with file inventory, image orientation, personal information flags, findings, and a pass, warn, or fail verdict.

OriginalShow the original description

Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.

See how to install

Good for

  • Checking a DICOM series before conversion
  • Reviewing image orientation before AI inference
  • Recording preflight findings in JSON
  • Checking headers for personal information flags

Files included (10)

  • SKILL.md3.4 KB
  • BENCHMARK.md7.4 KB
  • evals/evals.json2.5 KB
  • fixtures/generate_fixtures.py2.0 KB
  • scripts/preflight_series.py12.6 KB
  • skill_manifest.yaml3.6 KB
  • skill-card.md4.1 KB
  • skill.oms.sig5.7 KB
  • tests/test_preflight_series.py2.0 KB
  • validators/output_schema.json1.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

DICOM Series Preflight

Purpose

  • Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.
  • Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
  • Manifest I/O: inputs are dicom_dir; outputs are preflight_json.

Instructions

  • Read skill_manifest.yaml before changing arguments, side effects, or validation gates.
  • Run scripts/preflight_series.py through the documented command below; keep outputs under a caller-provided run directory.
  • If a host agent exposes run_script, use run_script("scripts/preflight_series.py", args=[...]); otherwise run the Bash/Python command shown below.
  • Check the emitted JSON and paired verifier guidance before treating the run as evidence.

Available Scripts

ScriptPurposeArguments
scripts/preflight_series.pyPrimary entrypoint declared by skill_manifest.yaml.PATH_TO_DICOM_DIR

Prerequisites

  • Runtime requirements: Python packages listed in runtime.side_effects.pip_packages.
  • NiBabel 5.4 or newer is required so extreme-oblique axes remain labeled consistently across reorientation.
  • Run commands from the repository root unless an existing section below says otherwise.

Limitations

  • Header-only; does not decode pixel data or detect burnt-in PHI.
  • Canonical orientation gate assumes LPS-derived CT axcodes L,P,S.
  • Compressed transfer syntax and multi-frame instances are warned, not decoded.
  • Single-directory scan; does not reconcile multiple studies in one tree.
  • Not for clinical deployment, regulatory de-identification, autonomous diagnosis, production ingestion without a vetted converter.

Troubleshooting

ErrorCauseFix
Missing dependency or import errorRuntime package drift from skill_manifest.yaml.Install the packages declared in the manifest or use the documented setup command.
Empty or schema-invalid outputWrong input path, unsupported modality, or upstream failure.Re-run with a known fixture and inspect the wrapper JSON plus stderr.
Validation gate failureOutput violated a declared engineering invariant.Keep the failed evidence pack and use the gate message to repair inputs or wrapper code.

Scans a DICOM directory (one series per folder) without decoding pixels. Emits JSON with inventory, orientation axcodes, PHI flags, findings, and a preflight.verdict of pass, warn, or fail.

python scripts/preflight_series.py PATH_TO_DICOM_DIR

Pair with verifiers/dicom_preflight_quality_v1 for a trusted preflight pack:

make run-trusted SKILL=dicom_series_preflight \
  FIXTURE=skills/dicom-series-preflight/fixtures/clean_no_phi \
  OUT=runs/dicom_preflight_demo

Flagship workflow:

make run-workflow \
  WORKFLOW=examples/workflows/dicom_preflight_gate.yaml \
  WORKFLOW_INPUT=skills/dicom-series-preflight/fixtures/clean_no_phi \
  WORKFLOW_OUT=runs/dicom_preflight_gate

Not for de-identification, private-tag review, or clinical clearance.

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