Read, modify, and anonymize DICOM files via pydicom Dataset objects and metadata.
npx skills add https://github.com/jackspace/ClaudeSkillz --skill pydicom
Please help me install this Agent Skill. Skill: pydicom Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/scientific-pkg-pydicom Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill pydicom
This Skill guides users on working with DICOM files in Python, enabling reading, modifying, anonymizing, converting pixel data, and managing DICOM metadata for medical imaging workflows.
Load a DICOM file, print patient name and modality, then anonymize and save a new file.
High-intent search queries and answers about installing and using this skill.
Use pydicom to load DICOM files as Dataset objects, then access metadata through ds attributes and file_meta. The library provides direct access to patient information, imaging modality, transfer syntax, and other header tags for medical imaging workflows.
Anonymization in pydicom involves identifying and removing PHI tags from the Dataset, then saving the modified file. Common targets include patient name, ID, birth date, and other identifiers; pydicom's tag access makes scripted removal straightforward for clinical research data sharing.
Yes, pydicom extracts pixel arrays from DICOM files and supports color space conversion, windowing, and multi-frame dataset handling. This enables image display, conversion to standard formats, and pixel-level modifications for medical imaging analysis.
Pydicom manages transfer syntax metadata and compressed pixel data through the Dataset and file_meta objects. The library supports reading various compression formats used in PACS systems, allowing you to work with different encoding schemes programmatically.
Pydicom allows scripted changes to Dataset attributes and tags, then saves the modified file while preserving DICOM structure. This supports workflows requiring metadata updates, tag corrections, or batch modifications across multiple files.
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