{"url":"/dataset/simnict","name":"SimNICT","full_name":null,"description_markdown":"SimNICT is the first dataset for training universal non-ideal measurement CT (NICT) enhancement models.\r\n\r\nThe dataset comprises over 10.9 million NICT-ICT image pairs, including low dose CT (LDCT), sparse view CT (SVCT), and limited angle CT (LACT), under varying defect degrees across whole-body regions.\r\n\r\nPaper: Imaging foundation model for universal enhancement of non-ideal measurement CT","description_withheld":null,"homepage":"https://huggingface.co/datasets/YutingHe-list/SimNICT","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY 4.0","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Medical Image Enhancement","url":"/task/medical-image-enhancement","datasets_with_task":"/datasets/task/medical-image-enhancement"}],"languages":[],"variants":["SimNICT"],"data_loaders":[],"num_papers_in_archive":0,"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."}