AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography

被引:38
作者
Fu, Huazhu [2 ]
Li, Fei [1 ]
Sun, Xu [3 ]
Cao, Xingxing [3 ]
Liao, Jingan [4 ]
Orlando, Jose Ignacio [5 ,6 ]
Tao, Xing [7 ]
Li, Yuexiang [8 ]
Zhang, Shihao [9 ]
Tan, Mingkui [9 ]
Yuan, Chenglang [10 ]
Bian, Cheng [8 ]
Xie, Ruitao [11 ]
Li, Jiongcheng [11 ]
Li, Xiaomeng [12 ]
Wang, Jing [12 ]
Geng, Le [13 ]
Li, Panming [13 ]
Hao, Huaying [14 ,15 ]
Liu, Jiang [15 ,16 ]
Kong, Yan [17 ]
Ren, Yongyong [17 ]
Bogunovic, Hrvoje [18 ]
Zhang, Xiulan [1 ]
Xu, Yanwu [3 ]
Zhang, Yichi [19 ]
Li, Nuhui [20 ]
Yang, Chunman [21 ]
Luo, Huang [22 ]
Li, Xingyi [23 ]
Deng, Feiyan [24 ]
Sun, Yi [23 ]
Zhou, Rouxi [23 ]
机构
[1] Sun Yat Sen Univ, Zhongshan Ophthalm Ctr, State Key Lab Ophthalmol, Guangzhou 510060, Peoples R China
[2] Incept Inst Artificial Intelligence, Abu Dhabi, U Arab Emirates
[3] Intelligent Healthcare Unit, Beijing, Peoples R China
[4] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou, Guangdong, Peoples R China
[5] Consejo Nacl Invest Cient & Tecn, Natl Sci & Tech Res Council, Buenos Aires, DF, Argentina
[6] Univ Nacl Ctr Prov Buenos Aires UNICEN, PLADEMA Inst, Yatiris Grp, Tandil, Argentina
[7] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou, Peoples R China
[8] Tencent Jarvis Lab, Shenzhen, Peoples R China
[9] South China Univ Technol, Sch Software Engn, Guangzhou, Peoples R China
[10] Shenzhen Univ, Hlth Sci Ctr, Sch Biomed Engn, Shenzhen, Peoples R China
[11] Shenzhen Univ, Sch Elect & Informat Engn, Shenzhen, Peoples R China
[12] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Hong Kong, Peoples R China
[13] Soochow Univ, Sch Elect & Informat Engn, Suzhou, Peoples R China
[14] Ningbo Univ, Ningbo, Zhejiang, Peoples R China
[15] Chinese Acad Sci, Ningbo Inst Ind Technol, Ningbo, Zhejiang, Peoples R China
[16] Southern Univ Sci & Technol, Shenzhen, Peoples R China
[17] Shanghai Jiao Tong Univ, Shanghai, Peoples R China
[18] Med Univ Vienna, Dept Ophthalmol, Lab Ophthalm Image Anal, Vienna, Austria
[19] SunYat Sen Univ, Sun Yat Sen Mem Hosp, Dept Ophthalmol, Guangzhou, Peoples R China
[20] Guangzhou Aier Eye Hosp, Guangzhou, Peoples R China
[21] GuiZhou Med Univ, Affiliated Hosp 2, Dept Ophthalmol, Kaili, Peoples R China
[22] Guangzhou Med Univ, Affiliated Trandit Chinese Med Hosp, Dept Ophthalmol, Guangzhou, Peoples R China
[23] Sun Yat Sen Univ, Zhongshan Ophthalm Ctr, Guangzhou, Peoples R China
[24] Trandit Chinese Med Hosp Guangdong Prov, Dept Ophthalmol, Guangzhou, Peoples R China
关键词
AS-OCT; Anterior chamber angle; Angle closure classification; Scleral spur localization; DIABETIC-RETINOPATHY; CHAMBER; CLASSIFICATION; VALIDATION; DISEASES; NETWORK; IMAGES; SYSTEM;
D O I
10.1016/j.media.2020.101798
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevated intraocular pressure and gradually lead to glaucomatous optic neuropathy and eventually to visual impairment and blindness. Anterior Segment Optical Coherence Tomography (AS-OCT) imaging provides a fast and contactless way to discriminate angle closure from open angle. Although many medical image analysis algorithms have been developed for glaucoma diagnosis, only a few studies have focused on AS-OCT imaging. In particular, there is no public AS-OCT dataset available for evaluating the existing methods in a uniform way, which limits progress in the development of automated techniques for angle closure detection and assessment. To address this, we organized the Angle closure Glaucoma Evaluation challenge (AGE), held in conjunction with MICCAI 2019. The AGE challenge consisted of two tasks: scleral spur localization and angle closure classification. For this challenge, we released a large dataset of 4800 annotated AS-OCT images from 199 patients, and also proposed an evaluation framework to benchmark and compare different models. During the AGE challenge, over 200 teams registered online, and more than 1100 results were submitted for online evaluation. Finally, eight teams participated in the onsite challenge. In this paper, we summarize these eight onsite challenge methods and analyze their corresponding results for the two tasks. We further discuss limitations and future directions. In the AGE challenge, the top-performing approach had an average Euclidean Distance of 10 pixels (10 mu m) in scleral spur localization, while in the task of angle closure classification, all the algorithms achieved satisfactory performances, with two best obtaining an accuracy rate of 100%. These artificial intelligence techniques have the potential to promote new developments in AS-OCT image analysis and image-based angle closure glaucoma assessment in particular. (C) 2020 Elsevier B.V. All rights reserved.
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页数:12
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