pathml

combined

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. Supports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference. Use for whole-slide H&E, CODEX, Vectra, Mesmer, HoVer-Net, and HACTNet workflows.

When to use

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

Skill page

Conflict

The K-Dense-AI copy is the only one that provides a version-pinned, reproducible installation and a correct, minimal API workflow for PathML 3.0.8 (using HESlide and SlideData.run). The other three copies (Vibe-Skills, medical-research-skills, OpenClaw-Medical-Skills) are nearly identical to each other but contain a critical API error: they use SlideData.from_slide() and Pipeline.run(), which the K-Dense copy explicitly states do not exist in the current stable release. They also recommend pathml[all], which the K-Dense copy warns against. Because the copies disagree on the core execution steps and installation constraints, crowning one would hide a real alternative (the incorrect API usage) that an agent might follow.