Extract and preprocess whole-slide-image tiles for digital pathology pipelines.
npx skills add https://github.com/wsxwj123/opencode-skills-backup --skill histolab-wsxwj123
Please help me install this Agent Skill. Skill: histolab Source: https://github.com/wsxwj123/opencode-skills-backup/tree/main/histolab Command: npx skills add https://github.com/wsxwj123/opencode-skills-backup --skill histolab-wsxwj123
Histolab provides a lightweight toolkit to process whole slide images by automatically detecting tissue, extracting representative tiles, and performing basic stain normalization to accelerate dataset preparation and quick tile-based analyses.
Load a slide, configure a RandomTiler with tile_size=(512, 512) and n_tiles=100 at level 0, then run the tiler to extract tiles.
High-intent search queries and answers about installing and using this skill.
Extract WSI tiles by loading a slide and configuring a tiler like RandomTiler with specific tile dimensions and counts. This automates tissue detection and tile extraction to build ready-to-use datasets for digital pathology workflows.
Tissue detection in digital pathology slides is best handled by applying automated tissue masking to isolate regions. This isolates relevant tissue areas from the whole slide image to accelerate dataset preparation and quick tile-based analyses.
Yes, you can sample specific informative regions by using the ScoreTiler to select the most representative areas. This tile extraction strategy targets high-information regions rather than basic grid coverage or random sampling.
Perform stain normalization on extracted WSI tiles by applying basic preprocessing hooks during the tile extraction pipeline. This ensures consistent color profiles across slides for quality control and downstream analysis.
No specific dependencies are required to process whole slide images, as the toolkit operates independently. You can load slides and configure tilers directly to automate tissue detection, tile extraction, and stain normalization pipelines.
Automated WSI tile extraction focuses on basic slide processing, tissue detection, and simple pipelines rather than complex transformations. It is designed for dataset preparation and quick slide QA rather than advanced clinical pathology diagnostics.
robinbarvaagProcess whole slide images and extract tissue tiles for deep learning datasets.
sanand0Process whole slide images for tissue detection, segmentation, and tile extraction.
jackspaceExtract informative tiles and detect tissue regions from whole slide images.
swaruplabAutomate whole-slide image tile extraction and preprocessing with tissue masking.
