dicom-metadata-extract
Used for extracting selected metadata from one DICOM file and flagging standard-tag PHI presence. Not for anonymization or clinical use.
git clone --depth 1 https://github.com/NVIDIA/skills /tmp/dicom-metadata-extract && cp -r /tmp/dicom-metadata-extract/skills/dicom-metadata-extract ~/.claude/skills/dicom-metadata-extractSKILL.md
# DICOM Metadata Extract
## Purpose
- Used for extracting selected metadata from one DICOM file and flagging standard-tag PHI presence. Not for anonymization or clinical use.
- Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
- Manifest I/O: inputs are `dicom_path`; outputs are `metadata_json`.
## Instructions
- Read `skill_manifest.yaml` before changing arguments, side effects, or validation gates.
- Run `scripts/extract_metadata.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/extract_metadata.py", args=[...])`; otherwise run the Bash/Python command shown below.
- Check the emitted JSON and run `medagent.verifiers.dicom_metadata_quality_v1` on evidence packs before treating the run as reviewed evidence.
## Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
| `scripts/extract_metadata.py` | Primary entrypoint declared by skill_manifest.yaml. | `PATH_TO_DICOM [--output OUT.json]` |
## Prerequisites
- Runtime requirements: Python packages listed in `runtime.side_effects.pip_packages`.
- Run commands from the repository root unless an existing section below says otherwise.
## Limitations
- Small PS3.15-inspired standard-tag subset only; not a complete Basic Application Confidentiality Profile implementation.
- Private tags not checked
- Burnt-in pixel PHI not detected
- Multi-frame handling minimal
- Not for clinical deployment, regulatory de-identification, autonomous diagnosis, patient-facing use.
## Troubleshooting
| Error | Cause | Fix |
|---|---|---|
| Missing dependency or import error | Runtime package drift from `skill_manifest.yaml`. | Install the packages declared in the manifest or use the documented setup command. |
| Empty or schema-invalid output | Wrong input path, unsupported modality, or upstream failure. | Re-run with a known fixture and inspect the wrapper JSON plus stderr. |
| Validation gate failure | Output violated a declared engineering invariant. | Keep the failed evidence pack and use the gate message to repair inputs or wrapper code. |
Reads one DICOM file with pydicom and emits JSON on stdout.
```bash
python scripts/extract_metadata.py PATH_TO_DICOM
python scripts/extract_metadata.py PATH_TO_DICOM --output result.json
```
Output includes `transfer_syntax`, `modality`, grouped study/series/image
metadata, `phi_present`, and `phi_tags_found`.
Use this as the smallest end-to-end example of a Medical AI Skills skill. Do not use
it for anonymization, private-tag review, pixel PHI detection, or clinical
interpretation.
For second-pass evidence review, generate a trusted run:
```bash
python -m eval_engine.run_trusted skills/dicom-metadata-extract \
--fixture skills/dicom-metadata-extract/fixtures/sample_ct.dcm \
--out runs/dicom_metadata_trusted
```>-
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
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