{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:13:55Z","timestamp":1777655635661,"version":"3.51.4"},"reference-count":85,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100013297","name":"Eurostars","doi-asserted-by":"publisher","award":["E12712"],"award-info":[{"award-number":["E12712"]}],"id":[{"id":"10.13039\/100013297","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008536","name":"Amazon Web Services","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008536","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tmi.2023.3313786","type":"journal-article","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T17:39:08Z","timestamp":1694799548000},"page":"542-557","source":"Crossref","is-referenced-by-count":60,"title":["AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge"],"prefix":"10.1109","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5908-8367","authenticated-orcid":false,"given":"Coen","family":"de Vente","sequence":"first","affiliation":[{"name":"Quantitative Healthcare Analysis (QurAI) Group, Informatics Institute, Universiteit van Amsterdam, Amsterdam, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4038-3945","authenticated-orcid":false,"given":"Koenraad A.","family":"Vermeer","sequence":"additional","affiliation":[{"name":"Rotterdam Ophthalmic Institute, The Rotterdam Eye Hospital, Rotterdam, The Netherlands"}]},{"given":"Nicolas","family":"Jaccard","sequence":"additional","affiliation":[{"name":"Project Orbis International Inc., New York, NY, USA"}]},{"given":"He","family":"Wang","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7907-3557","authenticated-orcid":false,"given":"Hongyi","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}]},{"given":"Firas","family":"Khader","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany"}]},{"given":"Daniel","family":"Truhn","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1060-4882","authenticated-orcid":false,"given":"Temirgali","family":"Aimyshev","sequence":"additional","affiliation":[{"name":"CMC Technologies LLP, Nur-Sultan, Kazakhstan"}]},{"given":"Yerkebulan","family":"Zhanibekuly","sequence":"additional","affiliation":[{"name":"CMC Technologies LLP, Nur-Sultan, Kazakhstan"}]},{"given":"Tien-Dung","family":"Le","sequence":"additional","affiliation":[{"name":"KBC, Brussels, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5992-1520","authenticated-orcid":false,"given":"Adrian","family":"Galdran","sequence":"additional","affiliation":[{"name":"Departament de Tecnologies de la Informació i les Comunicacions (DTIC), Universitat Pompeu Fabra, Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1953-3272","authenticated-orcid":false,"given":"Miguel \u00c1ngel Gonz\u00e1lez","family":"Ballester","sequence":"additional","affiliation":[{"name":"Departament de Tecnologies de la Informació i les Comunicacions (DTIC), Universitat Pompeu Fabra, Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5571-6220","authenticated-orcid":false,"given":"Gustavo","family":"Carneiro","sequence":"additional","affiliation":[{"name":"Australian Institute for Machine Learning AIML, University of Adelaide, Adelaide, SA, Australia"}]},{"given":"R. G.","family":"Devika","sequence":"additional","affiliation":[{"name":"College of Engineering Trivandrum, Thiruvananthapuram, India"}]},{"given":"Hrishikesh Panikkasseril","family":"Sethumadhavan","sequence":"additional","affiliation":[{"name":"Founding Minds Software, Thiruvananthapuram, India"}]},{"given":"Densen","family":"Puthussery","sequence":"additional","affiliation":[{"name":"Founding Minds Software, Thiruvananthapuram, India"}]},{"given":"Hong","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Zekang","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4941-4920","authenticated-orcid":false,"given":"Satoshi","family":"Kondo","sequence":"additional","affiliation":[{"name":"Muroran Institute of Technology, Muroran, Japan"}]},{"given":"Satoshi","family":"Kasai","sequence":"additional","affiliation":[{"name":"Niigata University of Health and Welfare, Niigata, Japan"}]},{"given":"Edward","family":"Wang","sequence":"additional","affiliation":[{"name":"Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4502-3663","authenticated-orcid":false,"given":"Ashritha","family":"Durvasula","sequence":"additional","affiliation":[{"name":"Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4775-1306","authenticated-orcid":false,"given":"J\u00f3nathan","family":"Heras","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, University of La Rioja, Logroño, Spain"}]},{"given":"Miguel \u00c1ngel","family":"Zapata","sequence":"additional","affiliation":[{"name":"Hospital Vall Hebron, Sant Cugat del Vallés, Barcelona, Spain"}]},{"given":"Teresa","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Optometry, Christian Doppler Laboratory for Artificial Intelligence in Retina, Medical University of Vienna, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4225-2156","authenticated-orcid":false,"given":"Guilherme","family":"Aresta","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Optometry, Christian Doppler Laboratory for Artificial Intelligence in Retina, Medical University of Vienna, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9168-0894","authenticated-orcid":false,"given":"Hrvoje","family":"Bogunovi\u0107","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology and Optometry, Christian Doppler Laboratory for Artificial Intelligence in Retina, Medical University of Vienna, Vienna, Austria"}]},{"given":"Mustafa","family":"Arikan","sequence":"additional","affiliation":[{"name":"Institute of Ophthalmology, University College London, London, U.K."}]},{"given":"Yeong Chan","family":"Lee","sequence":"additional","affiliation":[{"name":"Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea"}]},{"given":"Hyun Bin","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea"}]},{"given":"Yoon Ho","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3102-1595","authenticated-orcid":false,"given":"Abdul","family":"Qayyum","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, King’s College London, London, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3930-6600","authenticated-orcid":false,"given":"Imran","family":"Razzak","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2028-8972","authenticated-orcid":false,"given":"Bram","family":"van Ginneken","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine, Diagnostic Image Analysis Group (DIAG), Radboudumc, Nijmegen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8508-8985","authenticated-orcid":false,"given":"Hans G.","family":"Lemij","sequence":"additional","affiliation":[{"name":"Rotterdam Ophthalmic Institute, The Rotterdam Eye Hospital, Rotterdam, The Netherlands"}]},{"given":"Clara I.","family":"S\u00e1nchez","sequence":"additional","affiliation":[{"name":"Quantitative Healthcare Analysis (QurAI) Group, Informatics Institute, Universiteit van Amsterdam, Amsterdam, The Netherlands"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2014.05.013"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1097\/IJG.0000000000000389"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1111\/j.1755-3768.2012.02555.x"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2013.05.027"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2014.3192"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2015.7319578"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.18152"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2018.01.023"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2020.03.041,PMID:32703394"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s41433-019-0510-3"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376718"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IEMBS.2010.5626137"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CBMS.2011.5999143"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2012.0455"},{"issue":"1","key":"ref15","first-page":"1004","article-title":"A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis","volume":"2","author":"Sivaswamy","year":"2015","journal-title":"JSM Biomed. Imag. Data Papers"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.4.1.014503"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00934-2_8"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101570"},{"key":"ref19","article-title":"REFUGE2 challenge: A treasure trove for multi-dimension analysis and evaluation in glaucoma screening","author":"Fang","year":"2022","journal-title":"arXiv:2202.08994"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102938"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1177\/193229680900300315"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2009.09.026"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.xops.2023.100300"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1117\/1.JBO.19.4.046006"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1177\/0272989X8900900307"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1111\/j.1755-3768.2007.00947.x"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1111\/j.1755-3768.2011.02355.x"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/S1076-6332(00)80381-5"},{"key":"ref29","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref30","article-title":"Decoupled weight decay regularization","author":"Loshchilov","year":"2017","journal-title":"arXiv:1711.05101"},{"key":"ref31","article-title":"Sharpness-aware minimization for efficiently improving generalization","author":"Foret","year":"2020","journal-title":"arXiv:2010.01412"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01070"},{"key":"ref34","article-title":"AutoAugment: Learning augmentation policies from data","author":"Cubuk","year":"2018","journal-title":"arXiv:1805.09501"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00081"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ISBIC56247.2022.9854585"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ISBIC56247.2022.9854758"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ISBIC56247.2022.9854763"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_26"},{"key":"ref41","article-title":"An image is worth 16\u00d716 words, what is a video worth?","author":"Sharir","year":"2021","journal-title":"arXiv:2103.13915"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3188710"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref44","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref45","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref46","first-page":"10096","article-title":"EfficientNetv2: Smaller models and faster training","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref47","volume-title":"YOLOv5 by ultralytics","author":"Jocher","year":"2020"},{"key":"ref48","volume-title":"Glaucoma Detection Algorithm for the Artificial Intelligence for Robust Glaucoma Screening Challenge","author":"Aimyshev","year":"2022"},{"key":"ref49","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020","journal-title":"arXiv:2010.11929"},{"key":"ref50","volume-title":"Combination of Supervised Learning and Unsupervised Learning to Detect Ungradable Images in the Airogs Challenge","author":"Le","year":"2022"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref52","volume-title":"Open-Set Glaucoma Screening From Eye Fundus Images: Domain Knowledge to the Rescue","author":"Galdran","year":"2022"},{"key":"ref53","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref54","volume-title":"A Self-Supervised Approach for Glaucoma Screening","author":"Puthussery","year":"2022"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2018.2889273"},{"key":"ref57","volume-title":"Deep Learning for Referable Glaucoma Screening and Out-of-Distribution Detection","author":"Yang","year":"2022"},{"key":"ref58","article-title":"Computer aided diagnosis and out-of-distribution detection in glaucoma screening using color fundus photography","author":"Kondo","year":"2022","journal-title":"arXiv:2202.11944"},{"key":"ref59","first-page":"22614","article-title":"Revisiting ResNets: Improved training and scaling strategies","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Bello"},{"key":"ref60","first-page":"21464","article-title":"Energy-based out-of-distribution detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Liu"},{"key":"ref61","first-page":"144","article-title":"ReAct: Out-of-distribution detection with rectified activations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Sun"},{"key":"ref62","volume-title":"Ensemble Network for Glaucoma Screening in Airogs Challenge","author":"Wang","year":"2022"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref64","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref66","article-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2013","journal-title":"arXiv:1312.6114"},{"key":"ref67","volume-title":"A Good Closed-Set Classifier is all You Need for the Airogs Challenge","author":"Heras","year":"2022"},{"key":"ref68","article-title":"Open-set recognition: A good closed-set classifier is all you need?","author":"Vaze","year":"2021","journal-title":"arXiv:2110.06207"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1968.tb00722.x"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref71","volume-title":"Multi-Model Ensemble for Robust Glaucoma Screening","author":"Arikan","year":"2022"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref73","volume-title":"Classification for Referable Glaucoma With Fundus Photographs Using Multimodal Deep Learning","author":"Lee","year":"2022"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"},{"key":"ref76","volume-title":"ConvNeXts and Vision Transformer Based Framework for Glaucoma Screening","author":"Qayyum","year":"2022"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"ref78","first-page":"1179","article-title":"Single layer predictive normalized maximum likelihood for out-of-distribution detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Bibas"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12419"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102762"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.02007"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-25066-8_9"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00181"},{"issue":"7","key":"ref84","first-page":"2041","article-title":"Glaucomatous features in fundus photographs of eyes with \u2018referable glaucoma\u2019 of a large population based labeled data set for training an artificial intelligence (AI) algorithm for glaucoma screening","volume":"63","author":"Lemij","year":"2022","journal-title":"Investigative Ophthalmol. Vis. Sci."},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1016\/j.preteyeres.2021.101034"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/10379496\/10253652.pdf?arnumber=10253652","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T03:33:54Z","timestamp":1705030434000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10253652\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":85,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2023.3313786","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}