{"url":"/dataset/kits19","name":"KiTS19","full_name":"The 2019 Kidney and Kidney Tumor Segmentation Challenge","description_markdown":"The 2021 Kidney and Kidney Tumor Segmentation challenge (abbreviated KiTS21) is a competition in which teams compete to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy.\r\n\r\n[The 2021 Kidney and Kidney Tumor Segmentation Challenge](https://kits21.kits-challenge.org/)\r\n\r\n[The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge](https://arxiv.org/abs/1912.01054)","description_withheld":null,"homepage":"https://kits21.kits-challenge.org","introduced_date":"2019-12-02","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"3D","url":"/datasets/modality/3d"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Semi-Supervised Semantic Segmentation","url":"/task/semi-supervised-semantic-segmentation","datasets_with_task":"/datasets/task/semi-supervised-semantic-segmentation"},{"name":"3D Semantic Segmentation","url":"/task/3d-semantic-segmentation","datasets_with_task":"/datasets/task/3d-semantic-segmentation"},{"name":"3D Medical Imaging Segmentation","url":"/task/3d-medical-imaging-segmentation","datasets_with_task":"/datasets/task/3d-medical-imaging-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["KiTS19"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semi-supervised-semantic-segmentation-on-34","task":"Semi-Supervised Semantic Segmentation","dataset_variant":"KiTS19","rows":1,"metrics":["Avg DSC"],"first_row_in_archive_order":{"model":"PatchCL","paper":"/paper/pseudo-label-guided-contrastive-learning-for","metrics":{"Avg DSC":"0.919"},"code_links":[{"title":"HiLab-git/SSL4MIS","url":"https://github.com/HiLab-git/SSL4MIS"},{"title":"hritam-98/patchcl-medseg","url":"https://github.com/hritam-98/patchcl-medseg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/pseudo-label-guided-contrastive-learning-for","title":"Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical Image Segmentation","date":"2023-01-01","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}