Pydicom

About

Empower your medical imaging workflows with Pydicom, the specialized capability for interacting with DICOM files, the universal standard for healthcare imaging. This skill facilitates complex operations such as extracting pixel data from CT, MRI, and X-ray scans, modifying header metadata, and performing robust anonymization to protect patient privacy. Ideal for healthcare developers and researchers, it bridges the gap between raw medical datasets and actionable insights by providing implementation patterns for image conversion, sequence handling, and multi-slice volume reconstruction.

Key Features

• Comprehensive metadata extraction and tag manipulation using attribute or tag notation
• 2,066 GitHub stars
• Secure anonymization workflows to remove or replace Protected Health Information (PHI)
• Multi-frame processing and 3D volume reconstruction from related image series
• Advanced pixel data handling including VOI LUT windowing and color space conversion
• Decompression and management of diverse DICOM transfer syntaxes and compression formats

Use Cases

• Preparing medical imaging datasets for machine learning research through standardized anonymization
• Building automated radiology workflows and PACS integration tools
• Converting DICOM files to common image formats like PNG or JPEG for easier visualization and sharing