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AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge

文献类型：期刊论文

作者de Vente, Coen29,30,31; Vermeer, Koenraad A.28; Jaccard, Nicolas27; Wang, He25,26; Sun, Hongyi24; Khader, Firas23; Truhn, Daniel23; Aimyshev, Temirgali22; Zhanibekuly, Yerkebulan22; Le, Tien-Dung21
刊名IEEE TRANSACTIONS ON MEDICAL IMAGING
出版日期2024
卷号43期号:1页码:542-557
关键词Color fundus photography glaucoma screening out-of-distribution detection retina robustness
ISSN号0278-0062
DOI10.1109/TMI.2023.3313786
英文摘要The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models for glaucoma screening from CFPs have shown promising results in laboratory settings, their performance decreases significantly in real-world scenarios due to the presence of out-of-distribution and low-quality images. To address this issue, we propose the Artificial Intelligence for Robust Glaucoma Screening (AIROGS) challenge. This challenge includes a large dataset of around 113,000 images from about 60,000 patients and 500 different screening centers, and encourages the development of algorithms that are robust to ungradable and unexpected input data. We evaluated solutions from 14 teams in this paper and found that the best teams performed similarly to a set of 20 expert ophthalmologists and optometrists. The highest-scoring team achieved an area under the receiver operating characteristic curve of 0.99 (95% CI: 0.98-0.99) for detecting ungradable images on-the-fly. Additionally, many of the algorithms showed robust performance when tested on three other publicly available datasets. These results demonstrate the feasibility of robust AI-enabled glaucoma screening.
资助项目Eurostars
WOS研究方向Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
语种英语
WOS记录号WOS:001158081600018
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/38814]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者de Vente, Coen
作者单位1.Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW 3125, Australia
2.Kings Coll London, Dept Biomed Engn, London, England
3.Mayo Clin, Dept Artificial Intelligence & Informat, Jacksonville, FL 32224 USA
4.Sungkyunkwan Univ, Samsung Med Ctr, Samsung Adv Inst Hlth Sci & Technol SAIHST, Dept Digital Hlth, Seoul 06351, South Korea
5.Samsung Med Ctr, Res Inst Future Med, Seoul 06351, South Korea
6.UCL, Inst Ophthalmol, London EC1V 9EL, England
7.Med Univ Vienna, Dept Ophthalmol & Optometry, Christian Doppler Lab Artificial Intelligence Reti, A-1090 Vienna, Austria
8.UPRetina, Barcelona 08195, Spain
9.Hosp Valle De Hebron, Sant Cugat Del Valles 08195, Spain
10.Univ La Rioja, Dept Math & Comp Sci, Logrono 26004, Spain
推荐引用方式
GB/T 7714		 de Vente, Coen,Vermeer, Koenraad A.,Jaccard, Nicolas,et al. AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2024,43(1):542-557.
APA de Vente, Coen.,Vermeer, Koenraad A..,Jaccard, Nicolas.,Wang, He.,Sun, Hongyi.,...&Sanchez, Clara I..(2024).AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.IEEE TRANSACTIONS ON MEDICAL IMAGING,43(1),542-557.
MLA de Vente, Coen,et al."AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge".IEEE TRANSACTIONS ON MEDICAL IMAGING 43.1(2024):542-557.

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来源：计算技术研究所

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