extracting-dicom-metadata
适用于影像入库前的PHI审计与报告文本抽取，支持结构化元数据。
可能暴露患者识别信息并需处理大文件与专有像素数据。
读取DICOM头与SR内容，提取影像研究元数据与报告文本并标注PHI。
把 DICOM 文件里的头信息和 DICOM‑SR 报告树里的人类可读报告抽出来，提取 study/series 的元数据和报告文本并标注可能的 PHI。影像入库或送给 OpenMed 做去标识与文本分析前用，能告诉你哪些 header tags（PatientName 等）必须被擦除。支持用 pydicom 读取标签，能同时处理 CT/MR/CR/US 等模态和放射学 SR。
▸ 展开 SKILL.md 英文原文
Reads DICOM file headers and DICOM-SR (Structured Report) content to pull study/series metadata and embedded report text, and flags PHI carried in header tags. Use before OpenMed processing when ingesting imaging data (CT/MR/CR/US, radiology SR) and you need the report narrative de-identified and analyzed, plus a list of header tags that must be scrubbed. Hand SR/report text to openmed.deidentify and openmed.analyze_text; use pydicom to read tags. Trigger keywords: DICOM, pydicom, DICOM-SR, structured report, PatientName, study metadata, PACS, radiology report, PS3.
帮我安装这个 skill：https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extracting-dicom-metadata/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extracting-dicom-metadata/SKILL.md"# Extracting DICOM Metadata & Report Text for OpenMed DICOM (Digital Imaging and Communications in Medicine) files carry far more than pixels: a **header** of tagged attributes (patient, study, series, equipment) and, for **DICOM-SR (Structured Reports)**, a content tree holding the actual radiology/cardiology *report text*. Two jobs sit here: pull the report narrative for NLP, and **flag the PHI in the header** so it gets scrubbed. This skill does both, then hands narrative to OpenMed. Header tags are read with `pydicom` (external, MIT-licensed); de-identification of the extracted text is OpenMed's. ## When to use - You ingest DICOM from PACS/VNA or a research archive and want the SR rep