How does it handle 3D medical volumes?

It provides patterns for reading entire directories of DICOM slices and stacking them into 3D NumPy arrays using metadata spacing information.

Can I use this for HIPAA compliance?

While the skill provides anonymization workflows for removing PHI, users should verify their specific workflows against institutional security and privacy policies.

Can it convert DICOM to PNG or JPEG?

Yes, the skill includes code patterns and specialized scripts to normalize pixel data and save it using Pillow or Matplotlib.

Does this skill handle compressed DICOM files?

Yes, it includes instructions and helper scripts for handling common compression formats like JPEG 2000 and RLE, though additional libraries like pylibjpeg may be required.

Pydicom Medical Imaging

Name: Pydicom Medical Imaging
Author: pur3v4d3r

bypur3v4d3r

•

数据科学与机器学习

Processes, modifies, and analyzes DICOM medical imaging files using the pydicom library.

This skill enables Claude to handle DICOM (Digital Imaging and Communications in Medicine) files, the industry standard for medical imaging data like CT, MRI, and X-rays. It provides structured workflows for reading metadata, extracting pixel arrays for visualization with NumPy and Matplotlib, anonymizing patient data for research, and converting medical scans into standard image formats like PNG or JPEG. It is essential for developers working on radiology workflows, medical AI training, or PACS integration.

主要功能

01Automated medical data anonymization to remove Protected Health Information (PHI)

02Extract pixel data for NumPy-based image processing and visualization

03Support for compressed DICOM formats including JPEG 2000 and RLE

04Batch processing of DICOM series for 3D volume reconstruction

05Read and write DICOM datasets with full metadata and tag access

061 GitHub stars

使用场景

01Preparing medical datasets for machine learning and AI model training

02Anonymizing patient records for compliant data sharing and research purposes

03Developing radiology workflow automation and PACS software integrations

主要功能

01Automated medical data anonymization to remove Protected Health Information (PHI)

02Extract pixel data for NumPy-based image processing and visualization

03Support for compressed DICOM formats including JPEG 2000 and RLE

04Batch processing of DICOM series for 3D volume reconstruction

05Read and write DICOM datasets with full metadata and tag access

061 GitHub stars

使用场景

01Preparing medical datasets for machine learning and AI model training

02Anonymizing patient records for compliant data sharing and research purposes

03Developing radiology workflow automation and PACS software integrations