{"url":"/dataset/les-av","name":"LES-AV","full_name":null,"description_markdown":"This data set comprises 22 fundus images with their corresponding manual annotations for the blood vessels, separated as arteries and veins.\r\nIt also include labels for glaucomatous / healthy, differentiating between normal tension glaucoma (NAG) and primary open angle glaucoma (POAG).\r\n\r\nFurther information about the data set is provided in our MICCAI 2018 paper:\r\n\r\nOrlando, J. I., Breda, J. B., van Keer, K., Blaschko, M. B., Blanco, P. J., & Bulant, C. A. (2018). Towards a glaucoma risk index based on simulated hemodynamics from fundus images. MICCAI 2018.\r\n\r\nPlease, cite the corresponding paper in case you use this data on a scientific publication. Any commercial usage is forbidden.\r\nThis data set can only be used for scientific purposes.","description_withheld":null,"homepage":"https://figshare.com/articles/dataset/LES-AV_dataset/11857698","introduced_date":"2018-09-01","introduced_date_note":null,"introduced_by":null,"license":{"name":"GPL","url":"https://www.gnu.org/licenses/gpl-3.0.html"},"modalities":[],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"},{"name":"Segmentation","url":"/task/segmentation","datasets_with_task":"/datasets/task/segmentation"},{"name":"Artery/Veins Retinal Vessel Segmentation","url":"/task/artery-veins-retinal-vessel-segmentation","datasets_with_task":"/datasets/task/artery-veins-retinal-vessel-segmentation"}],"languages":[],"variants":["LES-AV"],"data_loaders":[{"repo":"https://github.com/rubenhx/av-segmentation","url":"https://github.com/rubenhx/av-segmentation","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/artery-veins-retinal-vessel-segmentation-on-2","task":"Artery/Veins Retinal Vessel Segmentation","dataset_variant":"LES-AV","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"RRWNet","paper":"/paper/rrwnet-recursive-refinement-network-for","metrics":{"Accuracy":"0.9481"},"code_links":[{"title":"j-morano/rrwnet","url":"https://github.com/j-morano/rrwnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/classification-on-les-av","task":"Classification","dataset_variant":"LES-AV","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"RRWNet","paper":"/paper/rrwnet-recursive-refinement-network-for","metrics":{"Accuracy":"0.9481"},"code_links":[{"title":"j-morano/rrwnet","url":"https://github.com/j-morano/rrwnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rrwnet-recursive-refinement-network-for","title":"RRWNet: Recursive Refinement Network for effective retinal artery/vein segmentation and classification","date":"2024-02-05","rows_on_this_dataset":2,"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."}