alterlab-pydicom

Read, anonymize, convert, and manage DICOM datasets with pydicom.

58|9|Updated Mar 16, 2026

Search Tags:#metadata #conversion #anonymization #dicom #medical-imaging #pydicom #pixel-data

Ready to run

npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-pydicom

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alterlab-pydicom
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/clinical-research/alterlab-pydicom
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-pydicom

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Reading, modifying, and securely handling DICOM files can be challenging due to sensitive PHI and varied pixel data formats. This skill provides practical guidance and workflows to read, anonymize, convert, and manage DICOM datasets with pydicom.

Core Features & Use Cases

Read DICOM files and access metadata
Anonymize sensitive PHI in DICOM datasets
Convert DICOM pixel data to standard image formats
Modify metadata and handle compressed transfer syntaxes

Quick Start

Load a DICOM file into the workspace and request anonymization and conversion of its pixel data.

Frequently Asked Questions about alterlab-pydicom

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

FAQPage Schema

How do I anonymize DICOM files to remove sensitive patient health information?▼

You can anonymize DICOM files by using pydicom to read the dataset and modify or remove specific metadata tags containing sensitive PHI. This ensures datasets are securely handled for clinical research and radiology QA workflows.

How do I convert DICOM pixel data to standard image formats using Python?▼

You can convert DICOM pixel data by reading the dataset with pydicom and processing the pixel arrays using numpy and Pillow. This allows you to export medical imaging data into standard image formats for further analysis.

Does pydicom support reading DICOM files with compressed transfer syntaxes?▼

Yes, pydicom supports reading and modifying DICOM files with compressed transfer syntaxes. The skill provides workflows to handle varied pixel data formats and extract metadata from these compressed datasets.

What is the best way to extract and manage metadata from medical imaging datasets?▼

The best way to extract metadata from medical imaging datasets is loading the DICOM files into a Python environment using pydicom. This allows direct access to metadata fields for preparation tasks and research workflows.

Can I use pydicom with numpy and Pillow for radiology QA workflows?▼

Yes, you can use pydicom alongside numpy and Pillow for radiology QA workflows. This combination allows you to read DICOM datasets, manipulate pixel data arrays, and convert images for quality assurance tasks.

Why does handling DICOM datasets in Python require specific libraries like pydicom?▼

Handling DICOM datasets requires specific libraries like pydicom because medical imaging files contain complex metadata structures and varied pixel data formats that standard file readers cannot parse or securely anonymize.