dicom-metadata-extract

Extract DICOM header metadata and PHI-presence indicators into structured JSON.

Updated Apr 16, 2026

Search Tags:#metadata #privacy #dicom #medical-imaging #pydicom #phi #data-testing

Ready to run

npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill dicom-metadata-extract

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dicom-metadata-extract
Source: https://github.com/sayalinvidia/sayali-skills-test/tree/main/skills/dicom-metadata-extract
Command: npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill dicom-metadata-extract

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pydicom, typer, and includes scripts (resource) components.

What problem does it solve?

Extract DICOM header metadata and a PHI-presence indicator from a single DICOM file to support engineering workflows that require visibility into sensitive data without performing de-identification.

Core Features & Use Cases

Reads DICOM headers and outputs a structured JSON payload including modality, study, series, and image metadata, plus phi_present and phi_tags_found fields.
Flags PHI presence based on a standard subset of DICOM PS3.15 basic-profile tags and includes a phi_scope_disclaimer to outline scope and limitations.
Use Case: engineers validating PHI handling in non-clinical pipelines or during data release checks.

Quick Start

Run the skill on a DICOM file to produce a JSON payload containing modality, study/series/image metadata, and PHI flags.

Frequently Asked Questions about dicom-metadata-extract

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I extract DICOM metadata and check for PHI presence in a medical imaging file?▼

To extract DICOM metadata and check for PHI presence, this skill uses pydicom to read the file header and returns a structured JSON payload containing modality, study, series, image fields, and a phi_present indicator based on DICOM PS3.15 basic-profile tags.

Does pydicom support identifying Protected Health Information tags in DICOM headers?▼

Yes, pydicom reads the DICOM headers, and this skill flags PHI presence by checking against a standard subset of DICOM PS3.15 basic-profile tags, returning phi_present and phi_tags_found fields for validation.

Can I use this DICOM metadata extraction for clinical data de-identification workflows?▼

No, you cannot use this skill for clinical data de-identification workflows because it explicitly does not perform de-identification; it only extracts metadata and returns a phi_scope_disclaimer outlining the limitations of its PHI detection scope.

What is the best way to validate PHI handling in non-clinical DICOM pipelines?▼

The best way to validate PHI handling in non-clinical DICOM pipelines is to run this skill on a file to produce a JSON payload with phi_present and phi_tags_found fields, enabling engineers to review sensitive data visibility without altering the original file.

What DICOM header fields are included in the JSON metadata extraction output?▼

The JSON metadata extraction output includes modality, study, series, and image metadata fields, alongside the phi_present boolean, phi_tags_found list, and a phi_scope_disclaimer to support engineering testing scenarios.

Why does my DICOM metadata extraction show a phi_scope_disclaimer in the output?▼

A phi_scope_disclaimer appears in the DICOM metadata extraction output to explicitly outline the scope and limitations of the PHI detection mechanism, reminding users that the skill checks a subset of PS3.15 basic-profile tags and does not perform de-identification.