
DICOM Metadata Extract
OfficialFreeEfficiently extract metadata from DICOM files.
Free · Opens the source repo
What DICOM Metadata Extract does
DICOM Metadata Extract is a specialized tool designed for developers and researchers working with medical imaging data. It allows users to extract selected metadata from individual DICOM files, providing essential information such as transfer syntax, modality, and the presence of protected health information (PHI) tags. This skill is particularly useful for those needing to analyze DICOM files without engaging in clinical applications or anonymization processes, as it strictly adheres to metadata extraction without delving into patient data privacy or compliance issues.
The tool operates by utilizing a Python script, extract_metadata.py, which can be executed with a simple command line. Users need to provide the path to the DICOM file, and the output will be a JSON object containing relevant metadata. This output includes grouped study, series, and image metadata, along with flags indicating whether PHI is present and which standard tags were found. The skill is intended for environments where metadata extraction is required for analysis, quality assurance, or educational purposes.
While DICOM Metadata Extract is a powerful tool for metadata extraction, it does come with limitations. It is not designed for comprehensive clinical use, regulatory de-identification, or detection of private tags and burnt-in pixel PHI. Users should be aware that the tool only addresses a small subset of standard tags and does not support multi-frame handling extensively. Thus, it is best suited for scenarios where basic metadata extraction suffices, and not for those requiring in-depth analysis or clinical deployment.
In summary, DICOM Metadata Extract is an essential skill for developers and researchers in the medical imaging field who need to extract and analyze metadata from DICOM files efficiently. By following the provided instructions and adhering to the limitations outlined, users can leverage this tool to enhance their workflows without the complexities of clinical data management.
When to use it
Use this skill when you need to extract metadata from a DICOM file for analysis or quality assurance purposes, without engaging in clinical applications.
When not to use it
Avoid using this skill for anonymization, clinical deployment, or when needing to check for private tags and burnt-in pixel PHI.
What you can build with it
Analyzing Medical Imaging Data
Use this skill to extract essential metadata from DICOM files for research purposes, aiding in the analysis of medical imaging data.
Quality Assurance in Imaging Workflows
Incorporate this tool into your imaging workflows to ensure that metadata is correctly extracted and validated before further processing.
Educational Purposes
Utilize this skill in educational settings to teach students about DICOM file structures and metadata extraction without engaging in clinical applications.
How to install DICOM Metadata Extract
View source1. Install with the skills CLI
npx skills add nvidia/skills/dicom-metadata-extract --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by nvidiaDICOM 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 aremetadata_json.
Instructions
- Read
skill_manifest.yamlbefore changing arguments, side effects, or validation gates. - Run
scripts/extract_metadata.pythrough the documented command below; keep outputs under a caller-provided run directory. - If a host agent exposes
run_script, userun_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_v1on 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.
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:
python -m eval_engine.run_trusted skills/dicom-metadata-extract \
--fixture skills/dicom-metadata-extract/fixtures/sample_ct.dcm \
--out runs/dicom_metadata_trusted
Frequently asked questions about DICOM Metadata Extract
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