{"url":"/dataset/ctpelvic1k","name":"CTPelvic1K","full_name":null,"description_markdown":"Curates a large pelvic CT dataset pooled from multiple sources and different manufacturers, including 1, 184 CT volumes and over 320, 000 slices with different resolutions and a variety of the above-mentioned appearance variations.\r\n\r\nSource: [Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models](/paper/deep-learning-to-segment-pelvic-bones-large)","description_withheld":null,"homepage":"https://github.com/ICT-MIRACLE-lab/CTPelvic1K","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-learning-to-segment-pelvic-bones-large","title":"Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models","first_author":"Pengbo Liu","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["CTPelvic1K"],"data_loaders":[{"repo":"https://github.com/ICT-MIRACLE-lab/CTPelvic1K","url":"https://github.com/ICT-MIRACLE-lab/CTPelvic1K","frameworks":[]}],"num_papers_in_archive":10,"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."}