Agent skill · research science · aiskillstore
pathml
Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.
Why this skill is useful
Adds specialized functions for loading, processing, and analyzing diverse whole-slide image formats and machine learning models specific to pathology data.
What it needs
Requires python installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
PathML Overview PathML is a comprehensive Python toolkit for computational pathology workflows, designed to facilitate machine learning and image analysis for whole-slide pathology images. The framework provides modular, composable tools for loading diverse slide formats, preprocessing images, constructing spatial graphs, training deep learning models, and analyzing multiparametric imaging data from technologies like CODEX and multiplex immunofluorescence. When to Use This Skill Apply this skill for: Loading and processing whole-slide images (WSI) in various proprietary formats Preprocessing H&E stained tissue images with stain normalization Nucleus detection, segmentation, and classification workflows Building cell and tissue graphs for spatial analysis Training or deploying machine learning models (HoVer-Net, HACTNet) on pathology data Analyzing multiparametric imaging (CODEX, Vectra, MERFISH) for spatial proteomics Quantifying marker expression from multiplex immunofluorescence Managing large-scale pathology datasets with HDF5 storage Tile-based analysis and stitching operations Core Capabilities PathML provides six major capability areas documented in detail within reference files: 1. Image Loading & Formats Load whole-slide images from 160+ proprietary formats including Aperio SVS, Hamamatsu NDPI, Leica SCN, Zeiss ZVI, DICOM, and OME-TIFF. PathML automatically handles vendor-specific formats and provides unified interfaces for accessing image pyramids, metadata, and regions of interest. See: references/imageloading.md for supported formats, loading strategies, and working with different slide types. 2. Preprocessing Pipelines Build modular preprocessing pipelines by composing transforms for image manipulation, quality control, stain normalization, tissue detection, and mask operations. PathML's Pipeline architecture enables reproducible, scalable preprocessing across large datasets. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/pathml