Individual skill
histolab
Extracts tiles and preprocesses H&E whole slide images with the histolab Python library (OpenSlide), covering slide inspection, tissue masks (TissueMask, BiggestTissueBoxMask), RandomTiler, GridTiler and ScoreTiler extraction, image and morphological filters, and Macenko or Reinhard stain normalization. Use when building a tile dataset from WSI files for deep learning. Use when detecting tissue and excluding background or pen annotations. Use when previewing tile locations and exporting tile CSV reports. Use when normalizing stain variation across slides. Not for spatial proteomics, multiplexed imaging, or deep learning pipelines; use pathml for those.
plugins/KalarisLabs/research-agent-skills/skills/histolab/SKILL.md
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SKILL.mdcore · 11,810 bytesSKILL.mdcore · 11,810 bytesSKILL.mdcore · 11,810 bytesSKILL.mdcore · 11,810 bytesreferences/core_capabilities.mddoc · 9,454 bytesreferences/filters_preprocessing.mddoc · 13,640 bytesreferences/slide_management.mddoc · 5,183 bytesreferences/tile_extraction.mddoc · 11,297 bytesreferences/tissue_masks.mddoc · 7,232 bytesreferences/typical_workflows.mddoc · 4,939 bytesreferences/visualization.mddoc · 14,027 bytes
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# Histolab
## Overview
Histolab is a Python library for processing whole slide images (WSI) in digital pathology. It automates tissue detection, extracts informative tiles from gigapixel images, and prepares datasets for deep learning pipelines. The library handles multiple WSI formats, implements sophisticated tissue segmentation, and provides flexible tile extraction strategies.
## Installation
Install OpenSlide system libraries first ([OpenSlide download](https://openslide.org/download/)), then install histolab:
```bash
uv pip install histolab
```
