Medical Imaging

This skill provides comprehensive documentation for accessing the National Cancer Institute's Imaging Data Commons (IDC), a public repository of cancer imaging data. It teaches users how to query, download, and visualize radiology and pathology images (CT, MR, PET, slide microscopy) using the idc-index Python package, with guides for BigQuery advanced queries and DICOMweb integration.

PathML is a full-featured computational pathology toolkit for analyzing whole-slide pathology images. It supports 160+ slide formats, provides preprocessing pipelines for H&E stain normalization and tissue detection, includes pre-trained models for nucleus segmentation, enables graph-based spatial analysis, and supports multiparametric imaging platforms like CODEX and Vectra for spatial proteomics workflows.

Histolab is a documentation skill for the histolab Python library used in digital pathology. It provides comprehensive guidance on processing whole slide images (WSI), including tissue detection, tile extraction strategies, preprocessing filters, and visualization techniques for preparing datasets for deep learning pipelines.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.