The OCELOT dataset is a histopathology dataset designed to facilitate the development of methods that utilize cell and tissue relationships. The dataset comprises both small and large field-of-view (FoV) patches extracted from digitally scanned whole slide images (WSIs), with overlapping regions. The small and large FoV patches are accompanied by annotations of cells and tissues, respectively. The WSIs are sourced from the publicly available TCGA database and were stained using the H&E method before being scanned with an Aperio scanner. For more details, please check https://lunit-io.github.io/research/ocelot_dataset/. Before downloading the dataset, please carefully read and agree to the Terms and Conditions at https://lunit-io.github.io/research/ocelot_tc/. If you use the dataset, please cite the OCELOT dataset paper and the OCELOT 2023 challenge paper. ----------------------------------------------------------------------------------- Release note. In version 1.0.1, we exclude four test cases (586, 589, 609, 615) due to under-annotated issue.In version 1.0.0, we include images and annotations of validation and test splits.In version 0.1.2, we modified the coordinates of cell labels to range from 0 to 1023 (-1 from the previous coordinates).In version 0.1.1, we removed non-H&E stained patches from the dataset.

This dataset is used for OCELOT 2023 challenge (https://ocelot2023.grand-challenge.org/) at MICCAI 2023.