Can I automatically filter out background or slide artifacts?

Yes, Histolab includes TissueMask and BiggestTissueBoxMask classes that automatically identify tissue regions and exclude non-informative backgrounds or pen marks.

What tile extraction strategies are available in this skill?

You can use RandomTiler for diverse sampling, GridTiler for comprehensive coverage, or ScoreTiler to rank and extract tiles based on metrics like nuclei density.

Which whole slide image formats does Histolab support?

Histolab supports standard digital pathology formats including SVS, TIFF, and NDPI, utilizing pyramidal image structures for efficient high-resolution processing.

Does Histolab handle image preprocessing and filtering?

Yes, it provides a comprehensive suite of filters for color space conversions (RGB to HED/HSV), Otsu thresholding, and morphological operations to clean images before analysis.

How can I verify the extraction locations before running a job?

The skill provides locate_mask() and locate_tiles() methods to generate visual previews of masks and tile coordinates on slide thumbnails.

Histolab Digital Pathology

Name: Histolab Digital Pathology
Author: Microck

byMicrock

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数据科学与机器学习

Automates tissue detection and tile extraction from gigapixel histopathology images for computational pathology deep learning pipelines.

Histolab is a specialized Claude Code skill designed to streamline digital pathology workflows by providing a robust framework for processing Whole Slide Images (WSI). It enables users to handle massive gigapixel files in formats like SVS, TIFF, and NDPI, automating the complex tasks of tissue segmentation, artifact removal, and informative tile extraction. Whether you need systematic grid coverage or quality-driven selection based on nuclei density, Histolab provides the tools to transform raw medical slides into structured datasets ready for advanced machine learning analysis.

主要功能

0181 GitHub stars

02Multiple tile extraction strategies including Random, Grid, and Score-based sampling

03Support for multi-format Whole Slide Images (WSI) such as SVS, TIFF, and NDPI

04Extensive preprocessing filters for color space conversion and morphological operations

05Automated tissue detection and mask generation to exclude background and artifacts

06Integrated visualization tools for slide thumbnails, tissue masks, and tile locations

使用场景

01Automating the segmentation of tissue regions in gigapixel surgical pathology slides

02Preparing high-quality image datasets for training histopathology deep learning models

03Identifying and extracting the most informative regions of a slide using cellularity scoring

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills histolab

For use in Claude.ai and ChatGPT

Download Skill