histolab

Automate tissue detection and tile extraction from whole-slide images.

33.0k|3.2k|Updated Oct 19, 2025
One-click install
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill histolab-k-dense-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: histolab
Source: https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/histolab
Command: npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill histolab-k-dense-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Histolab streamlines whole-slide image analysis by automating tissue detection, tile extraction, and preprocessing to produce ready-to-use datasets for deep learning and research workflows.

Core Features & Use Cases

  • Tissue detection and masking with TissueMask and BiggestTissueBoxMask for flexible region selection
  • Tile extraction strategies (RandomTiler, GridTiler, ScoreTiler) at multiple pyramid levels
  • Flexible preprocessing pipelines using image and morphological filters
  • Visualization and debugging tools for masks, tile locations, and tile quality
  • Use Cases: preparing datasets for model training, rapid slide screening, and quality-controlled tissue quantification

Quick Start

Install histolab, load a sample slide, and run a basic RandomTiler to extract 100 tiles at level 0.

Frequently Asked Questions about histolab

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate tissue detection and tile extraction on whole-slide images?▼

Automate tissue detection and tile extraction on whole-slide images using configurable tilers and tissue masks to generate ready-to-use datasets for deep learning and image analysis.

What is the best way to extract tiles from WSI files for deep learning datasets?▼

The best way to extract tiles from WSI files is using RandomTiler, GridTiler, or ScoreTiler at multiple pyramid levels to produce reproducible, quality-controlled datasets for deep learning.

Does histolab support flexible region selection for tissue masking?▼

Yes, flexible region selection for tissue masking is supported using TissueMask and BiggestTissueBoxMask to accommodate diverse slide types and various analysis goals.

Can I apply image and morphological filters during WSI preprocessing?▼

Yes, you can apply image and morphological filters during WSI preprocessing through flexible pipelines to produce ready-to-use datasets for deep learning and image analysis.

How do I visualize tissue masks and tile locations for quality control?▼

Visualize tissue masks and tile locations using built-in debugging tools to verify tile quality and ensure reproducible tiling across diverse slide types and analysis goals.

What are the limitations of automated tile extraction for digital pathology workflows?▼

Limitations of automated tile extraction for digital pathology workflows include needing configurable tilers and tissue masks to accommodate diverse slide types and multiple stains for accurate region selection.