{"url":"/dataset/raos","name":"RAOS","full_name":"Rethinking Abdominal Organ Segmentation","description_markdown":"Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases.\r\n\r\nThis dataset consists of 413 real clinical CT scans and 413x9 MR scans, all 19 organs were annotated by a senior oncologist (MD. Wenjun Liao, 10 years experiment).\r\nsome challenging cases in clinical practice can help evaluate the generalization and robustness of deep learning methods.\r\nSome organ annotations not present in previous public datasets (such as prostate, seminal vesicles, etc).","description_withheld":null,"homepage":"https://github.com/luoxd1996/raos","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"GPL-3.0 license","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Biomedical","url":"/datasets/modality/biomedical"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Medical Image Segmentation","url":"/task/medical-image-segmentation","datasets_with_task":"/datasets/task/medical-image-segmentation"},{"name":"Volumetric Medical Image Segmentation","url":"/task/volumetric-medical-image-segmentation","datasets_with_task":"/datasets/task/volumetric-medical-image-segmentation"}],"languages":[],"variants":["RAOS"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}