{"url":"/dataset/inspire-avr-lunet-subset","name":"INSPIRE-AVR (LUNet subset)","full_name":null,"description_markdown":"This dataset contains 65 DFIs acquired from patients with POAG at the University of Iowa Hospitals and Clinics. DFIs were acquired using a 30° Zeiss fundus camera (Niemeijer et al 2011). The images were centered on the optic disc. The original DFIs resolution was 2392 × 2048. In order to benchmark LUNet on this dataset, the black border of the DFIs were padded to a squared resolution of 2048 × 2048 pixels and then resized to a 1444 × 1444 pixels resolution. From the resulting DFIs, 15 optic disc-centered DFIs were randomly selected to form the second external test set. No other additional metadata were provided in the open source dataset.","description_withheld":null,"homepage":"https://pvbm.readthedocs.io/en/latest/index.html","introduced_date":"2023-09-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/lunet-deep-learning-for-the-segmentation-of","title":"LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images","first_author":"Jonathan Fhima","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Retinal Vessel Segmentation","url":"/task/retinal-vessel-segmentation","datasets_with_task":"/datasets/task/retinal-vessel-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":["INSPIRE-AVR (LUNet subset)"],"data_loaders":[],"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-1","task":"Artery/Veins Retinal Vessel Segmentation","dataset_variant":"INSPIRE-AVR (LUNet subset)","rows":1,"metrics":["Average Dice (0.5*Dice_a + 0.5*Dice_v)"],"first_row_in_archive_order":{"model":"LUNet","paper":"/paper/lunet-deep-learning-for-the-segmentation-of","metrics":{"Average Dice (0.5*Dice_a + 0.5*Dice_v)":"75.6"},"code_links":[{"title":"aim-lab/LUNet","url":"https://github.com/aim-lab/LUNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/retinal-vessel-segmentation-on-inspire-avr","task":"Retinal Vessel Segmentation","dataset_variant":"INSPIRE-AVR (LUNet subset)","rows":1,"metrics":["Average Dice"],"first_row_in_archive_order":{"model":"LUNet","paper":"/paper/lunet-deep-learning-for-the-segmentation-of","metrics":{"Average Dice":"75.6"},"code_links":[{"title":"aim-lab/LUNet","url":"https://github.com/aim-lab/LUNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/lunet-deep-learning-for-the-segmentation-of","title":"LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images","date":"2023-09-11","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"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."}