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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Kidney Segmentation Dataset: Voxel-level Annotations for Renal Cell Carcinoma CT Imaging

Authors: de Boer, Sarah; Häntze, Hartmut; Ziegelmayer, Sebastian; van Ginneken, Bram; Prokop, Mathias; Bressem, Keno; Hering, Alessa;

Kidney Segmentation Dataset: Voxel-level Annotations for Renal Cell Carcinoma CT Imaging

Abstract

Associated publication: de Boer, Häntze, et al. Accessible and Reproducible Renal Cell Carcinoma Research Through Open-Sourcing Data and Annotations medRxiv (preprint). Background This dataset provides voxel-level segmentation annotations for CT imaging from three TCGA renal cell carcinoma (RCC) cohorts: clear cell (TCGA-KIRC), papillary (TCGA-KIRP), and chromophobe (TCGA-KICH). It was created to support accessible and reproducible AI research for RCC and addresses the common problem of TCGA imaging data lacking easily accessible public annotations. A total of 142 annotated CT scans from 101 patients are included (95 clear cell, 29 papillary, 18 chromophobe RCC). Dataset Contents File Description images\ NifTI (.nii.gz) files of CT images, converted from TCIA DICOM source data annotations\ NifTI (.nii.gz) segmentation masks, one per scan metadata.csv Case-level metadata including RCC subtype, patient demographics, and TCIA series identifiers. Reproduced from TCIA source collections (CC BY 3.0). manifest.tcia TCIA Data Retriever manifest. Opening this file with the NBIA Data Retriever will download the original DICOM images directly from TCIA. Segmentation label map: 0 - Background 1 - Kidney 2 - Tumor 3 - Cyst The specific RCC subtype for each case (clear cell, papillary, or chromophobe) is provided in metadata.csv. License Segmentation annotations: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). NIfTI images and metadata.csv are derived from or reproduced from TCIA source collections (see Attribution below), which are published under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/). Citation If you use this dataset, please cite our paper (preprint until published): de Boer, Häntze, et al. Accessible and Reproducible Renal Cell Carcinoma Research Through Open-Sourcing Data and Annotations. medRxiv. If a peer-reviewed version is available, please cite that instead. Additionally, please cite the following TCIA source collections and include the TCGA disclaimer: Akin, O., et al. (2016). The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma Collection (TCGA-KIRC) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.V6PBVTDR Linehan, M., et al. (2016). The Cancer Genome Atlas Kidney Renal Papillary Cell Carcinoma Collection (TCGA-KIRP) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.ACWOGBEF Linehan, M. W., et al. (2016). The Cancer Genome Atlas Kidney Chromophobe Collection (TCGA-KICH) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.YU3RBCZN Acknowledgements This research is funded by the European Union under HORIZON-HLTH-2022: COMFORT (101079894). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them. The results published here are in whole or in part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.

Keywords

Renal Cell Carcinoma, Kidney cancer, Image Segmentation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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