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dicom-metadata-extract

by @nvidiav
4.3(120)

用于从单个DICOM文件中提取选定元数据,并标记标准标签中是否存在受保护健康信息(PHI),辅助医疗数据合规审查和初步筛查。提供标准化JSON输出,便于下游处理。不可用于匿名化或临床决策。

dicommetadataphihealthcarepydicomGitHub
安装方式
npx skills add https://github.com/nvidia/skills --skill dicom-metadata-extract
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Before / After 效果对比

1 组
使用前

用户需要手动浏览DICOM文件中的所有标签,识别可能包含PHI的标准标签,通常需要20分钟左右,且容易遗漏关键字段。

使用后

此技能自动提取元数据并标记PHI标签,将审查时间缩短至1分钟,并减少人为疏漏。

SKILL.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

ScriptPurposeArguments
scripts/extract_metadata.pyPrimary 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

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.

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

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安装量1.9K
评分4.3 / 5.0
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更新日期2026年9月17日
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创建2026年7月26日
最后更新2026年9月17日
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