{"type":"ScholarlyArticle","title":"Multimodal Retina Image Analysis Survey: Datasets, Tasks and Methods","authors":[{"name":"Hongwei Sheng","slug":"hongwei-sheng","given":"Hongwei","family":"Sheng","affiliation":""},{"name":"Heming Du","slug":"heming-du","given":"Heming","family":"Du","affiliation":""},{"name":"Xin Shen","slug":"xin-shen","given":"Xin","family":"Shen","affiliation":""},{"name":"Sen Wang","slug":"sen-wang","given":"Sen","family":"Wang","affiliation":""},{"name":"Xin Yu","slug":"xin-yu","given":"Xin","family":"Yu","affiliation":""}],"abstract":"Retina images provide a noninvasive view of the central nervous system and microvasculature, making it essential for clinical applications. \r\nChanges in the retina often indicate both ophthalmic and systemic diseases, aiding in diagnosis and early intervention.\r\nWhile deep learning algorithms have advanced retina image analysis, a comprehensive review of related datasets, tasks, and benchmarking is still lacking. \r\nIn this survey, we systematically categorize existing retina image datasets based on their available data modalities, and review the tasks these datasets support in multimodal retina image analysis. \r\nWe also explain key evaluation metrics used in various retina image analysis benchmarks.\r\nBy thoroughly examining current datasets and methods, we highlight the challenges and limitations in existing benchmarks and discuss potential research topics in the field.\r\nWe hope this work will guide future retina analysis methods and promote the shared use of existing data across different tasks.","doi":"10.24963/ijcai.2025/1182","url":"https://ijcai.org/proceedings/2025/1182","pdf":"https://ijcai.org/proceedings/2025/1182.pdf","markdown":"https://ijcai.org/proceedings/2025/1182.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1182","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Survey Track","track":"Survey Track","number":1182,"pages":{"first":10650,"last":10659},"keywords":["Computer Vision: CV: Multimodal learning","Multidisciplinary Topics and Applications: MTA: Health and medicine"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}