TCGA@Focus Dataset

<strong>Content</strong> A dataset of 1000 whole slide images from 52 types of organs was gathered from The Cancer Genome Atlas (TCGA) repository provided by the National Cancer Institute (NCI)/ National Institute of Health (NIH). Two different categories of focus were annotated on every region of interest in these WSIs; they were labelled "in-focus" and "out-focus" and given respective binary ground truth scores of "1" and "0". From these regions of interest, a dataset of 14,371 image patches was created. Of these patches, 11,328 are labelled in-focus, and 3,043 are labelled out-focus. The organ types were selected to be diverse in order to include a wide spectrum of tissue textures and colour information to enrich the dataset. <strong>More Information</strong> For more information, please refer to the following paper. <strong>Please cite this paper when using the dataset.</strong> <pre><code>@InProceedings{wang2020focuslitenn, title={FocusLiteNN: High Efficiency Focus Quality Assessment for Digital Pathology}, author={Wang, Zhongling and Hosseini, Mahdi and Miles, Adyn and Plataniotis, Konstantinos and Wang, Zhou}, booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2020}, year={2020}, publisher="Springer International Publishing" }</code></pre> For the full code released on GitHub, please visit the repository at: https://github.com/icbcbicc/FocusLiteNN/ <strong>Contact</strong> For questions, please contact: Mahdi Hosseini [e-mail] http://orcid.org/0000-0002-9147-0731