Convert whole-slide pathology images into ML-ready datasets with HDF5 storage.
npx skills add https://github.com/shushuzn/Rairos --skill pathml-shushuzn
Please help me install this Agent Skill. Skill: pathml Source: https://github.com/shushuzn/Rairos/tree/main/skills/pathml Command: npx skills add https://github.com/shushuzn/Rairos --skill pathml-shushuzn
PathML reduces the time and expertise required to go from whole-slide pathology images to reliable computational outputs by providing end-to-end tooling for loading, preprocessing, segmentation, graph building, and dataset storage.
Use the PathML skill to load a whole-slide image, generate tiles, run a pipeline that performs tissue detection followed by H&E stain normalization, and then access the produced tissue mask and processed tiles.
High-intent search queries and answers about installing and using this skill.
Whole-slide pathology images are converted into ML-ready datasets by orchestrating loading, preprocessing, segmentation, and graph construction into configurable pipelines that output HDF5-backed tiles, masks, and features for batch ML training.
Yes, H&E stain normalization and tissue detection can be composed into a single preprocessing pipeline. You can configure transforms to sequentially handle tissue masking, stain normalization, denoising, and artifact labeling on whole-slide images.
Yes, multiplex imaging workflows support CODEX, Vectra, and MERFISH formats. The process handles cycle collapsing, nucleus/cell segmentation using Mesmer-based workflows, and marker quantification for downstream spatial analysis.
Building spatial graphs from cell segmentation results involves converting segmented cells into graph representations using kNN, radius, Delaunay, or contact connectivity options, generating graph-ready features suitable for downstream graph neural networks.
You can load whole-slide images across 160+ common vendor formats, DICOM, and OME-TIFF. This allows you to read WSI pyramids and regions of interest seamlessly for computational pathology preprocessing and analysis.
jackspaceExtract informative tiles and detect tissue regions from whole slide images.
JosephWoodallBuild and train graph neural networks with PyTorch Geometric.
tassiovaleExtract and preprocess whole slide image tiles with tissue detection and stain normalization.
silversteinConvert whole-slide pathology images into tiles, masks, graphs, and quantitative outputs.
