extracting-dicom-metadata SKILL.md skillA

extracting-dicom-metadata from maziyarpanahi/openmed is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add maziyarpanahi/openmed/extracting-dicom-metadata@v1.0

Pins v1.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
maziyarpanahi/openmed
Path
skills/extracting-dicom-metadata/SKILL.md
Versions recorded
1
Latest version
v1.0, committed Jul 20, 2026
Size
7,209 bytes
Repository stars
5,784
License
Apache-2.0

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…

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 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 report
  text mined with clinical NLP.
- You must enumerate PHI-bearing header tags before sharing/exporting images.
- You have DICOM-SR objects (e.g. radiology measurements + impression) whose
  content tree contains the dictated report.

## DICOM headers in one minute

Every attribute has a **tag** `(gggg,eeee)` (group, element), a **VR** (value
representation, e.g. `PN` person name, `DA` date, `UI` UID), and a value. PHI
clusters in well-known tags:

| Tag | Name | VR | Notes |
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add maziyarpanahi/openmed/extracting-dicom-metadata@sha256:98af880320ca169b

The line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_2kjn5haeui5pblwc.svg)](https://markdownregistry.com/a/art_2kjn5haeui5pblwc)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jul 20, 2026.

versioncommittedcommitsizeaudit
v1.0 latest2026-07-20 74f7d6b 7,209 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (7209 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

maziyarpanahi/openmed · 5,784 stars · license Apache-2.0 · pushed 2026-11-07 · branch master

API

GET https://markdownregistry.com/api/v1/artifacts/art_2kjn5haeui5pblwc
GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/extracting-dicom-metadata
GET https://markdownregistry.com/api/v1/blob/98af880320ca169b9de779a4d9d963b74916c1a7a37680e549b3ce4cd9df7cdf

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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