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