How do I anonymize patient data using this skill?

The skill includes specific workflows and scripts to remove or replace Protected Health Information (PHI) tags such as PatientName, PatientID, and BirthDate.

Can this skill handle compressed DICOM files?

Yes, it provides guidance on using specific handlers like pylibjpeg and GDCM to decompress and process various transfer syntaxes like JPEG2000 and RLE.

Can I convert DICOM to standard image formats?

Absolutely. The skill includes patterns for normalizing pixel values and using the Pillow library to save DICOM data as PNG, JPEG, or TIFF.

Is NumPy required for pixel manipulation?

Yes, the skill utilizes NumPy for efficient handling of pixel arrays, which is the standard approach for medical image processing in Python.

Pydicom Medical Imaging

Name: Pydicom Medical Imaging
Author: Activer007

byActiver007

Ciencia de Datos y ML

Read, write, and process medical imaging data in the DICOM standard format using Python.

Acerca de

This skill provides comprehensive capabilities for working with DICOM (Digital Imaging and Communications in Medicine) files, the global standard for healthcare imaging. It enables Claude to assist with reading and modifying medical metadata, extracting pixel data for analysis, and performing critical tasks like anonymizing patient information for research. Whether you are building radiology workflows, processing CT/MRI volumes, or integrating with PACS systems, this skill offers the implementation patterns and best practices needed to handle medical datasets efficiently using the Pydicom library.

Características Principales

Handle complex transfer syntaxes and compressed DICOM data
0 GitHub stars
Read and write DICOM files across various modalities (CT, MRI, X-ray, Ultrasound)
Extract and manipulate pixel data using NumPy and Matplotlib
Manage nested DICOM sequences and structured report data
Automate DICOM anonymization for HIPAA-compliant data sharing

Casos de Uso

Anonymizing medical datasets for research and machine learning training
Building automated pipelines for multi-slice volume reconstruction and voxel analysis
Converting DICOM scans to standard PNG or JPEG formats for reporting

Acerca de

Características Principales

Handle complex transfer syntaxes and compressed DICOM data
0 GitHub stars
Read and write DICOM files across various modalities (CT, MRI, X-ray, Ultrasound)
Extract and manipulate pixel data using NumPy and Matplotlib
Manage nested DICOM sequences and structured report data
Automate DICOM anonymization for HIPAA-compliant data sharing

Casos de Uso

Anonymizing medical datasets for research and machine learning training
Building automated pipelines for multi-slice volume reconstruction and voxel analysis
Converting DICOM scans to standard PNG or JPEG formats for reporting