{"url":"/dataset/mm-whs-2017","name":"MM-WHS 2017","full_name":"MM-WHS 2017","description_markdown":"The **MM-WHS 2017** dataset is a dataset for multi-modality whole heart segmentation. It provides 20 labeled and 40 unlabeled CT volumes, as well as 20 labeled and 40 unlabeled MR volumes. In total there are 120 multi-modality cardiac images acquired in a real clinical environment.","description_withheld":null,"homepage":"https://zmiclab.github.io/projects/mmwhs/","introduced_date":null,"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 Medical Image Segmentation","url":"/task/semi-supervised-medical-image-segmentation","datasets_with_task":"/datasets/task/semi-supervised-medical-image-segmentation"},{"name":"Heart Segmentation","url":"/task/heart-segmentation","datasets_with_task":"/datasets/task/heart-segmentation"}],"languages":[],"variants":["Multi-Modality Whole Heart Segmentation Challenge 2017","MM-WHS 2017"],"data_loaders":[{"repo":"https://github.com/jacobzhaoziyuan/MT-UDA","url":"https://github.com/jacobzhaoziyuan/MT-UDA","frameworks":["pytorch"]}],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semi-supervised-medical-image-segmentation-on","task":"Semi-supervised Medical Image Segmentation","dataset_variant":"MM-WHS 2017","rows":2,"metrics":["DSC"],"first_row_in_archive_order":{"model":"ACINet","paper":"/paper/addressing-class-imbalance-in-semi-supervised","metrics":{"DSC":"81.5"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/addressing-class-imbalance-in-semi-supervised","title":"Addressing Class Imbalance in Semi-supervised Image Segmentation: A Study on Cardiac MRI","date":"2022-08-31","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/an-embarrassingly-simple-consistency","title":"An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation","date":"2022-02-01","rows_on_this_dataset":1,"code_links":1,"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."}