Automate computational pathology workflows with WSI loading, preprocessing, graph construction, and ML.
npx skills add https://github.com/swaruplab/operon --skill pathml-swaruplab
Please help me install this Agent Skill. Skill: pathml Source: https://github.com/swaruplab/operon/tree/main/src-tauri/protocols/pathml Command: npx skills add https://github.com/swaruplab/operon --skill pathml-swaruplab
PathML consolidates loading, preprocessing, graph construction, and machine learning into a single, cohesive workflow for computational pathology, reducing setup time and engineering effort.
Install PathML and run a sample preprocessing workflow on a test slide to begin end-to-end pathology analyses.
High-intent search queries and answers about installing and using this skill.
This toolkit consolidates WSI loading, modular preprocessing, cellular graph construction, and ML model training into a single computational pathology workflow, reducing setup time and engineering effort.
Yes, the unified loader supports multiparametric imaging formats including CODEX, Vectra, and MERFISH alongside 160+ standard WSI formats. This enables integrated spatial analysis across diverse imaging modalities.
Yes, pathology ML models like HoVer-Net and HACTNet integrate natively with PyTorch for training and support ONNX export for deployment. This streamlines the model lifecycle from training to inference in production environments.
Managing large WSI datasets requires scalable data infrastructure. This toolkit uses HDF5 and DVC integration to handle large-scale computational pathology datasets efficiently during batch processing and machine learning workflows.
Stain normalization and tissue detection are executed through modular preprocessing pipelines. The toolkit provides customizable steps for stain normalization, nucleus detection, quality control, and feature extraction on whole-slide images.
Constructing cellular and tissue graphs is essential for extracting single-cell and tissue-level spatial insights. This approach enables spatial analysis when investigating complex tissue microenvironments in CODEX, MERFISH, or standard H&E pathology datasets.
jackspaceAnalyze whole-slide pathology images and multiparametric imaging data for computational pathology workflows.
HopeArtOrgConvert JAX/Python ML models to ONNX format via Google Colab notebooks.
biomaps-infraAutomate tissue detection and tile extraction from whole slide images.
robotlearning123Load whole-slide images, preprocess, and construct spatial graphs for pathology.
