histolab
CommunityProcess whole slide images efficiently.
Education & Research#bioinformatics#image analysis#histopathology#whole slide imaging#digital pathology#tile extraction
AuthorRowtion
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the complex and time-consuming process of analyzing large whole slide images (WSIs) in digital pathology, enabling researchers and students to extract meaningful data without manual intervention.
Core Features & Use Cases
- Automated Tile Extraction: Extracts informative tiles from gigapixel WSIs for downstream analysis.
- Tissue Detection & Masking: Identifies and isolates tissue regions, filtering out background.
- Flexible Preprocessing: Applies various filters for stain normalization and artifact removal.
- Use Case: A researcher needs to train a deep learning model on H&E stained tissue slides. This Skill can automatically detect tissue regions, extract thousands of representative tiles, and save them in a format suitable for model training.
Quick Start
Use the histolab skill to extract 100 random tiles of size 512x512 from the slide file 'slide.svs'.
Dependency Matrix
Required Modules
histolabnumpypillowmatplotlibscikit-image
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: histolab Download link: https://github.com/Rowtion/Bioclaw/archive/main.zip#histolab Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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