{"url":"/dataset/emidec","name":"EMIDEC","full_name":"MICCAI 2020 EMIDEC","description_markdown":"The **MICCAI 2020 EMIDEC** dataset is a dataset for classifying normal and pathological cases from the clinical information with or without DE-MRI, and secondly to automatically detect the different relevant areas (the myocardial contours, the infarcted area and the permanent microvascular obstruction area (no-reflow area)) from a series of short-axis DE-MRI covering the left ventricle. The segmentation allows one to make a quantification of the MI, in absolute value (mm3) or percentage of the myocardium.\r\n\r\nThe database consists of 150 exams (all from different patients) divided into 50 cases with normal MRI after injection of a contrast agent and 100 cases with myocardial infarction (and then with a hyperenhanced area on DE-MRI), whatever their inclusion in the cardiac emergency department. Along with MRI, clinical characteristics are provided to distinguish normal and pathological cases. The training set has 100 cases.\r\n\r\nLalande, A.; Chen, Z.; Decourselle, T.; Qayyum, A.; Pommier, T.; Lorgis, L.; de la Rosa, E.; Cochet, A.; Cottin, Y.; Ginhac, D.; Salomon, M.; Couturier, R.; Meriaudeau, F. Emidec: A Database Usable for the Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI. Data 2020, 5, 89.\r\ndoi: https://doi.org/10.3390/data5040089","description_withheld":null,"homepage":"http://emidec.com/","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":["EMIDEC"],"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":"2026-09-25T09:33:49+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."}