pathml
CommunityUnlock pathology insights with advanced image analysis.
Education & Research#deep learning#cell segmentation#stain normalization#whole slide imaging#multiplex imaging#computational pathology
AuthorRowtion
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill streamlines complex computational pathology workflows, enabling researchers and clinicians to analyze whole-slide images (WSI) and multiparametric data efficiently, reducing manual effort and accelerating discovery.
Core Features & Use Cases
- WSI Loading & Preprocessing: Supports 160+ slide formats, stain normalization, and artifact removal.
- Cell Segmentation & Analysis: Advanced tools for nucleus detection, cell segmentation (e.g., using Mesmer), and marker quantification.
- Spatial Omics Integration: Handles CODEX, Vectra, and MERFISH data for single-cell spatial proteomics and transcriptomics.
- Machine Learning Ready: Prepares data for deep learning models (e.g., HoVer-Net) and integrates with PyTorch.
- Use Case: Analyze multiplex immunofluorescence images to identify spatial relationships between immune cells and tumor cells, quantify marker expression, and discover novel biomarkers for cancer research.
Quick Start
Use the pathml skill to load the whole-slide image located at '/path/to/my_slide.svs' and generate a tissue mask.
Dependency Matrix
Required Modules
pathml
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: pathml Download link: https://github.com/Rowtion/Bioclaw/archive/main.zip#pathml Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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