Convert whole-slide and multiparametric pathology images into normalized tiles, masks, and model-ready datasets.
npx skills add https://github.com/dralkh/seerai --skill pathml-dralkh
Please help me install this Agent Skill. Skill: pathml Source: https://github.com/dralkh/seerai/tree/main/skills/pathml Command: npx skills add https://github.com/dralkh/seerai --skill pathml-dralkh
PathML removes the manual burden of analyzing large pathology and spatial biology datasets by turning raw slides and multiplex images into structured, machine-learning-ready outputs.
Use the pathml skill to load your pathology slides, run the appropriate preprocessing pipeline, and summarize the resulting masks, features, or cell data for downstream analysis.
High-intent search queries and answers about installing and using this skill.
To normalize staining and segment cells, load whole-slide images, apply preprocessing pipelines for stain normalization and tissue detection, then run cell segmentation to export model-ready datasets.
Spatial analysis of CODEX and Vectra multiplex images involves marker quantification, spatial graph construction, and structured feature export for computational pathology workflows.
Large-scale pathology slide batch processing uses Dask distributed execution to tile, normalize, and process over 160 slide formats into structured datasets efficiently.
PyTorch and ONNX model training and inference are supported on HDF5 datasets generated from normalized tiles, tissue masks, and segmented cell graphs for pathology workflows.
Computational pathology preprocessing supports 160-plus whole-slide formats including brightfield, DICOM, OME-TIFF, CODEX, and Vectra for tiling and stain normalization.
felixboehmLoad and preprocess whole-slide images for computational pathology workflows.
LeonChaoXLoad and preprocess whole-slide pathology images into ML-ready datasets.
Hung-3008Unify computational pathology workflows for whole-slide images and related data.
jackspaceAnalyze whole-slide pathology images and multiparametric imaging data for computational pathology workflows.
