Kidney CT Abnormality

<p>This data set is part of the public development data for&nbsp;the&nbsp;<a href="http://auc23.grand-challenge.org/">2023 Automated Universal Classification Challenge</a> (AUC23). The data set concerns the detection of kidney abnormalities in computed tomography (CT) scans and was originally introduced by&nbsp;<a href="https://zenodo.org/record/8014290">Humpire-Mamani et al. (2023)</a>. Data was&nbsp;restructured in compliance with the&nbsp;<a href="https://auc23.grand-challenge.org/">AUC23</a>&nbsp;challenge format.</p> <p>Images are&nbsp;3D tensors:</p> <ul> <li>0:&nbsp;3D CT scan</li> </ul> <p>Classification labels:</p> <ul> <li>0: Normal</li> <li>1: Abnormal</li> </ul> <p>imagesTr (root folder with all patients and studies)<br> &nbsp; &nbsp; ├── kidneyabnormalityKiTS-0000_0000.mha &nbsp;(3D CT&nbsp;for study 0)<br> &nbsp;&nbsp; &nbsp;├── kidneyabnormalityKiTS-0001_0000.mha &nbsp;(3D CT&nbsp;for study 1)<br> &nbsp; &nbsp; ├──&nbsp;...</p> <p>Please cite the following data set if you are using the kidney CT abnormality data&nbsp;:</p> <p>Gabriel E. Humpire-Mamani, Luc Builtjes, Colin Jacobs, Bram van Ginneken, Mathias Prokop, &amp; Ernst Th. Scholten. (2023). Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8014290</p>