{"id":5590,"date":"2023-09-04T03:10:50","date_gmt":"2023-09-04T03:10:50","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/c4kc-kits\/"},"modified":"2023-09-13T11:58:48","modified_gmt":"2023-09-13T11:58:48","slug":"c4kc-kits","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/c4kc-kits\/","title":{"rendered":"C4KC-KITS"},"featured_media":7830,"template":"","citation-tax":[],"cancer_types":["Kidney Cancer"],"citations":[4462,4463,2925],"collection_doi":"10.7937\/TCIA.2019.IX49E8NX","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[5014,5015],"full_export":"

Summary<\/h2>

<\/span>This collection contains CT scans and segmentations from subjects from the training set of the 2019 Kidney and Kidney Tumor Segmentation Challenge<\/a> (KiTS19). The challenge aimed to accelerate progress in automatic 3D semantic segmentation by releasing a dataset of CT scans for 210 patients with manual semantic segmentations of the kidneys and tumors in the corticomedullary phase. The imaging was collected during routine care of patients who were treated by either partial or radical nephrectomy at the University of Minnesota Medical Center. Many of the CT scans were acquired at referring institutions and are therefore heterogeneous in terms of scanner manufacturers and acquisition protocols. Semantic segmentations were performed by students under the supervision of an experienced urologic cancer surgeon.Protocol<\/strong><\/p>

Please refer to the data descriptor manuscript for a comprehensive account of the data collection and annotation process - arXiv:1904.00445<\/a>.\u00a0The Clinical Trial Time Point is calculated from Day of Surgery.<\/p>

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Acknowledgements<\/h3>

We would like to acknowledge the following institutions for their support of the data collection and associated challenge:<\/p>