Reads, writes, and manipulates DICOM medical imaging data and metadata for healthcare and research applications.
The Pydicom skill for Claude Code enables developers to work seamlessly with Digital Imaging and Communications in Medicine (DICOM) files, the global standard for medical imaging. It provides robust implementation patterns for extracting pixel data from CT, MRI, and X-ray scans, managing complex metadata tags, and ensuring data privacy through automated anonymization. Ideal for radiology workflows, PACS integration, and healthcare software development, this skill simplifies the handling of multi-frame images, compressed datasets, and 3D volume reconstruction within an AI-assisted development environment.
Características Principales
011 GitHub stars
02Read and write DICOM files across various modalities (CT, MRI, Ultrasound)
03Navigate and modify nested DICOM sequences and structured reports
04Anonymize Protected Health Information (PHI) for clinical research compliance
05Extract and manipulate pixel data with NumPy and Matplotlib integration
06Handle compressed transfer syntaxes including JPEG 2000 and RLE
Casos de Uso
01Building medical imaging analysis pipelines for machine learning models
02Anonymizing large patient datasets for secure data sharing and research
03Converting DICOM files to web-compatible formats like PNG, JPEG, or TIFF
