Skip to main content
skill CX Codex

dicom-metadata-extract — Claude Code skill: what it does

Runs a pydicom script on a single DICOM file to extract metadata and detect standard PHI tags. Useful for quick agent inspections of medical imaging files.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add NVIDIA/skills --skill dicom-metadata-extract -a claude-code
Open on GitHub

What dicom-metadata-extract does

Created by NVIDIA MedTech Team, this skill acts as an entrypoint for parsing single DICOM files. It invokes scripts/extract_metadata.py with an input dicom_path and prints JSON to stdout or writes it via --output. The resulting schema contains transfer_syntax, modality, study, series, and image structures, along with a phi_present flag and phi_tags_found.

The host agent can call the wrapper using run_script or execute it directly in Bash. Output verification relies on medagent.verifiers.dicom_metadata_quality_v1. You can also generate trusted runs using eval_engine.run_trusted against sample fixtures. Required Python dependencies are listed in skill_manifest.yaml.

Do not deploy this wrapper for clinical tasks or regulatory de-identification. Its inspection logic covers only a narrow subset of PS3.15 standard tags. Private tags and burnt-in pixel text remain unchecked.

What it helps with

  • extract metadata from a single DICOM file into JSON
  • inspect transfer syntax and modality attributes
  • flag standard PHI tags from a PS3.15 subset
  • verify run output with medagent.verifiers.dicom_metadata_quality_v1

Example prompts for the agent

  • Run scripts/extract_metadata.py on sample_ct.dcm and write the output to result.json.
  • Inspect study.dcm for PHI tags and show the extracted metadata JSON.
  • Execute python -m eval_engine.run_trusted on skills/dicom-metadata-extract with the CT fixture.

How to install dicom-metadata-extract

1Skills CLI (Vercel)

npx skills add NVIDIA/skills --skill dicom-metadata-extract -a claude-code

2Manually: put the files in place

~/.claude/skills/dicom-metadata-extract/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/dicom-metadata-extract/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about dicom-metadata-extract

How do I install dicom-metadata-extract in Claude Code?

Run npx skills add NVIDIA/skills --skill dicom-metadata-extract -a claude-code. The file will be placed in ~/.claude/skills/dicom-metadata-extract/SKILL.md.

What does dicom-metadata-extract do?

It executes a Python script with pydicom to extract study, series, and modality attributes from one DICOM file while flagging basic PHI tags.

Can this skill be used for regulatory de-identification?

No. It inspects only a small subset of standard PS3.15 tags and does not check private tags or burnt-in pixel PHI.

Source text

SKILL.md · Apache-2.0
---
name: dicom-metadata-extract
description: Used for extracting selected metadata from one DICOM file and flagging standard-tag PHI presence. Not for anonymization or clinical use.
license: Apache-2.0
allowed-tools: Bash
permissions: [file_read, file_write, shell]
metadata:
  author: 'NVIDIA MedTech Team'
  tags:
    - MedTech
    - DICOM
    - metadata
---

# 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
```

© NVIDIA MedTech Team · Apache-2.0 · NVIDIA/skills

Similar skills

Everything for Science and research →

From the same set194

digital-health-clinical-asr-build Curates clinical terms, synthesizes eval audio through Magpie TTS and writes a NeMo manifest. Stage 2 of the Clinical ASR Flywheel. CX Codex +1 1,900installs digital-health-clinical-asr-setup Sets up the environment for NVIDIA's Clinical ASR Flywheel, verifies the NVIDIA_API_KEY, installs Python dependencies, and runs an end-to-end smoke test. CX Codex +1 1,900installs dicom-series-to-volume Turns one CT DICOM series folder into an HU NIfTI volume plus a JSON summary with the affine. Handy before feeding scans to a segmentation model. CX Codex +1 1,900installs dicom-series-preflight Reads DICOM headers in a single series folder and returns JSON with a pass, warn or fail verdict before conversion or inference. CX Codex +1 1,900installs nemotron-policy-generator Turn moderation requirements or an existing policy into structured artifacts for NVIDIA Nemotron safety models. Useful when a project needs its rules prepared for model inference. CX Codex +1 1,900installs holoscan-install-source Builds and verifies NVIDIA Holoscan SDK 5.x from source using the repository container wrapper. Helps with Early Access branches and custom SDK components. CX Codex +1 1,800installs holoscan-install-debian Installs native C++ Debian packages of Holoscan SDK 5.x on Ubuntu 24.04 and checks that the bundled examples build. CX Codex +1 1,800installs holoscan-install-wheel Installs Holoscan SDK 5.x CUDA 13 Python wheels into an isolated venv and checks that the import works. CX Codex +1 1,800installs

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor