pydicom

Read, analyze, and modify DICOM datasets using Python and pydicom.

21|1|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/OwnLabAI/ownlab --skill pydicom-ownlabai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pydicom
Source: https://github.com/OwnLabAI/ownlab/tree/main/mart/skills/scientific-skills/pydicom
Command: npx skills add https://github.com/OwnLabAI/ownlab --skill pydicom-ownlabai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pydicom, numpy, pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill enables developers and researchers to read, write, anonymize, and manipulate medical imaging data stored in DICOM files using Python, facilitating access to pixel data, metadata, and image conversion for clinical and research workflows.

Core Features & Use Cases

  • Read DICOM files and access metadata via the pydicom library.
  • Modify, anonymize, or create DICOM datasets while preserving essential structure and relationships.
  • Convert pixel data to standard image formats and support basic visualization for quick inspection.

Quick Start

Install Python and pydicom, then read, modify, and extract data from DICOM files using this skill.

Frequently Asked Questions about pydicom

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

FAQPage Schema
How do I anonymize DICOM files in Python to remove patient metadata?

You can anonymize DICOM files in Python by modifying datasets to remove or replace patient metadata while preserving the essential structure. This skill supports anonymizing medical imaging data for clinical and research workflows.

How do I extract and convert DICOM pixel data to a standard image format?

Extract DICOM pixel data and convert it to standard image formats using Python with pydicom and pillow. This facilitates basic visualization and quick inspection of medical imaging data across radiology workflows.

What is the best way to read and modify DICOM metadata for clinical research?

Reading and modifying DICOM metadata is best handled via the pydicom library in Python. This skill enables accessing, altering, and managing dataset metadata directly for clinical research workflows.

Do I need numpy and pillow to process medical imaging data with pydicom?

You need Python and pydicom to read DICOM datasets, but numpy and pillow are optional dependencies required only for pixel processing and visualization tasks like converting medical imaging data to standard image formats.

Can I create new DICOM datasets from scratch while preserving structure?

Yes, you can create new DICOM datasets in Python while preserving essential structure and relationships. This skill allows modifying or generating DICOM files for medical imaging workflows.