histolab

To extract tissue-focused tiles from whole slide images, you can automate WSI preprocessing by generating binary tissue masks to exclude background and artifacts, then configuring a tiler across pyramid levels to output clean tile datasets for downstream analysis.

The best way to prepare a whole slide image dataset is to use score-based tiling combined with tissue masking to select high-quality, informative regions, exporting a balanced tile dataset alongside a CSV report of tile coordinates and scores for training.

Yes, you can sample specific regions from a WSI slide using Random tiling for exploratory sampling, Grid tiling for full-slide coverage, or Score-based tiling to select only the most informative tissue regions for your dataset preparation.

Yes, whole slide image preprocessing automatically removes pen marks and background artifacts by generating binary tissue masks that isolate the tissue and exclude unwanted regions during the tile extraction process.

You can visualize tissue masks and tile locations by enabling the visualization steps in the WSI preprocessing workflow, which produces quality-control outputs showing slide thumbnails, tissue masks, and tile locations for review.

Yes, you need to configure the tiler across pyramid levels when extracting tiles from whole slide images, as this step is required to manage the gigapixel slide structure and ensure accurate tissue-focused tile extraction.