{"url":"/dataset/refuge-challenge","name":"REFUGE Challenge","full_name":"Retinal Fundus Glaucoma Challenge","description_markdown":"REFUGE Challenge provides a data set of 1200 fundus images with ground truth segmentations and clinical glaucoma labels, currently the largest existing one.\r\n\r\nSource: [REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs](https://arxiv.org/pdf/1910.03667v1.pdf)\r\nImage Source: [Orlando et al](https://arxiv.org/pdf/1910.03667v1.pdf)","description_withheld":null,"homepage":"https://refuge.grand-challenge.org/Home2020/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/refuge-challenge-a-unified-framework-for","title":"REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs","first_author":"José Ignacio Orlando","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"name":"Optic Disc Segmentation","url":"/task/optic-disc-segmentation","datasets_with_task":"/datasets/task/optic-disc-segmentation"},{"name":"Fovea Detection","url":"/task/fovea-detection","datasets_with_task":"/datasets/task/fovea-detection"},{"name":"Optic Disc Detection","url":"/task/optic-disc-detection","datasets_with_task":"/datasets/task/optic-disc-detection"},{"name":"Optic Cup Segmentation","url":"/task/optic-cup-segmentation","datasets_with_task":"/datasets/task/optic-cup-segmentation"},{"name":"Optic Cup Detection","url":"/task/optic-cup-detection","datasets_with_task":"/datasets/task/optic-cup-detection"}],"languages":[],"variants":["REFUGE Challenge"],"data_loaders":[{"repo":"https://bitbucket.org/woalsdnd/refuge","url":"https://bitbucket.org/woalsdnd/refuge","frameworks":[]}],"num_papers_in_archive":14,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/optic-cup-segmentation-on-refuge-challenge","task":"Optic Cup Segmentation","dataset_variant":"REFUGE Challenge","rows":2,"metrics":["Dice"],"first_row_in_archive_order":{"model":"EfficientNet+U-Net++","paper":"/paper/optic-disc-cup-and-fovea-detection-from","metrics":{"Dice":"0.8762"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fovea-detection-on-refuge-challenge","task":"Fovea Detection","dataset_variant":"REFUGE Challenge","rows":1,"metrics":["Euclidean Distance (ED)"],"first_row_in_archive_order":{"model":"EfficientNet+U-Net++","paper":"/paper/optic-disc-cup-and-fovea-detection-from","metrics":{"Euclidean Distance (ED)":"35.18"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/optic-cup-detection-on-refuge-challenge","task":"Optic Cup Detection","dataset_variant":"REFUGE Challenge","rows":1,"metrics":["IoU"],"first_row_in_archive_order":{"model":"EfficientNet+U-Net++","paper":"/paper/optic-disc-cup-and-fovea-detection-from","metrics":{"IoU":"0.8128"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/optic-disc-detection-on-refuge-challenge","task":"Optic Disc Detection","dataset_variant":"REFUGE Challenge","rows":1,"metrics":["IoU"],"first_row_in_archive_order":{"model":"EfficientNet+U-Net++","paper":"/paper/optic-disc-cup-and-fovea-detection-from","metrics":{"IoU":"0.8847"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/medical-image-segmentation-using-squeeze-and","title":"Medical Image Segmentation Using Squeeze-and-Expansion Transformers","date":"2021-05-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":20,"samples_ran":13,"samples_unverified":7,"pointer_only_for_licence":20,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/optic-disc-cup-and-fovea-detection-from","title":"Optic Disc, Cup and Fovea Detection from Retinal Images Using U-Net++ with EfficientNet Encoder","date":"2020-11-20","rows_on_this_dataset":4,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":20,"samples_ran":13,"samples_unverified":7,"pointer_only_for_licence":20,"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."}