{"url":"/dataset/mhsma","name":"MHSMA","full_name":"The Modified Human Sperm Morphology Analysis","description_markdown":"The MHSMA dataset is a collection of human sperm images from 235 patients with male factor infertility. Each image is labeled by experts for normal or abnormal sperm acrosome, head, vacuole, and tail.\r\n\r\nThe training, validation, and test sets contain 1000, 240, and 300 images, respectively.\r\n\r\nImages are available in two different crop sizes: 128x128- and 64x64-pixel.\r\n\r\nPaper: [A novel deep learning method for automatic assessment of human sperm images](https://doi.org/10.1016/j.compbiomed.2019.04.030)","description_withheld":null,"homepage":"https://github.com/soroushj/mhsma-dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[],"languages":[],"variants":["MHSMA"],"data_loaders":[{"repo":"https://github.com/soroushj/mhsma-dataset","url":"https://github.com/soroushj/mhsma-dataset","frameworks":[]}],"num_papers_in_archive":2,"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."}