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histolab

Extract and preprocess whole slide image tiles from histopathology slides.

74|5|Updated Dec 10, 2025
Search Tags:#research#stain normalization#histopathology#tile extraction#wsi#tissue masking#slide visualization
One-click install
npx skills add https://github.com/dralkh/seerai --skill histolab-dralkh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: histolab
Source: https://github.com/dralkh/seerai/tree/main/skills/histolab
Command: npx skills add https://github.com/dralkh/seerai --skill histolab-dralkh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Histolab removes the manual burden of inspecting whole slide images, isolating tissue, and turning gigapixel pathology slides into manageable analysis-ready tiles.

Core Features & Use Cases

  • Slide inspection: Load WSI files, review dimensions, magnification, metadata, and thumbnails before processing.
  • Tissue detection and masking: Identify tissue regions, exclude background and artifacts, and customize masks for specific slide conditions.
  • Tile extraction: Sample regions with random extraction, cover tissue systematically with grids, or prioritize informative areas with scoring.
  • Preprocessing and normalization: Apply image filters, morphological cleanup, and stain normalization to improve consistency across slides.
  • Visualization and quality control: Preview masks, tile locations, extracted tiles, score distributions, and before/after filter results.
  • Use case: A pathology researcher can batch-process a slide collection, extract reproducible tiles for model training, and review the results visually before downstream analysis.

Quick Start

Use histolab to load a whole slide image, preview its tissue mask, and extract a small set of tiles from the attached pathology file.

Frequently Asked Questions about histolab

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

FAQPage Schema
How do I extract tiles from whole slide images for histopathology model training?▼

Tissue masking identifies tissue regions and excludes background and artifacts during whole slide image preprocessing. You can customize masks for specific slide conditions to ensure only relevant tissue areas are processed for downstream analysis.

Can I apply stain normalization to histopathology slides during preprocessing?▼

Yes, stain normalization is supported alongside image filters and morphological cleanup to improve consistency across histopathology slides. These preprocessing steps ensure normalized output tiles for dataset curation and quality control workflows.

Do I need OpenSlide to load whole slide images for tile extraction?▼

Yes, tile extraction requires OpenSlide-backed WSI access to load whole slide images for processing. This provides slide inspection capabilities including dimensions, magnification, metadata, and thumbnail previews before tissue masking and extraction.

What is the best way to detect tissue regions and exclude background in WSI files?▼

Tissue masking identifies tissue regions and excludes background and artifacts during whole slide image preprocessing. Customizable masks for specific slide conditions ensure only relevant tissue areas are processed for downstream analysis.

How does score-based tile extraction prioritize informative areas in histopathology slides?▼

Score-based tile extraction prioritizes informative areas by evaluating tissue regions and selecting tiles based on scoring criteria. This complements random extraction and grid coverage methods to ensure reproducible tile selection for research workflows.

Can I visualize tissue masks and tile locations before extracting tiles from pathology slides?▼

Yes, visualization and quality control features let you preview masks, tile locations, score distributions, and before/after filter results. This ensures you can review slide inspection outputs and extracted tiles before downstream analysis.

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