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Published March 23, 2023 | Version 1.0.1
Dataset Restricted

OCELOT: Overlapped Cell on Tissue Dataset for Histopathology

Creators

  • 1. Lunit

Description

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 make sure to carefully read and agree to the Terms and Conditions at (https://lunit-io.github.io/research/ocelot_tc/).

Also, please provide 1. name, 2. e-mail address, 3. organization/company name.

 

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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.

Notes

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

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Request access

If you would like to request access to these files, please fill out the form below.

You need to satisfy these conditions in order for this request to be accepted:

Before downloading the dataset, please make sure to carefully read and agree to the Terms and Conditions at (https://lunit-io.github.io/research/ocelot_tc/).

Also, please provide 1. name, 2. e-mail address, 3. organization/company name.

 

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Additional details

Related works

Cites
Preprint: 10.48550/arXiv.2303.13110 (DOI)