题名 | AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography |
作者 | Fu,Huazhu2; Li,Fei1; Sun,Xu3; Cao,Xingxing3; Liao,Jingan4; Orlando,José Ignacio5,6; Tao,Xing7; Li,Yuexiang8; Zhang,Shihao9; Tan,Mingkui9; Yuan,Chenglang10; Bian,Cheng8; Xie,Ruitao11; Li,Jiongcheng11; Li,Xiaomeng12; Wang,Jing12; Geng,Le13; Li,Panming13; Hao,Huaying14,15; Liu,Jiang15,16 ![]() ![]() |
通讯作者 | Zhang,Xiulan |
发表日期 | 2020-12-01
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DOI | |
发表期刊 | |
ISSN | 1361-8415
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EISSN | 1361-8423
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卷号 | 66 |
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 µm) 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. |
关键词 | |
相关链接 | [Scopus记录] |
收录类别 | |
语种 | 英语
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学校署名 | 其他
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WOS研究方向 | Computer Science
; Engineering
; Radiology, Nuclear Medicine & Medical Imaging
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WOS类目 | Computer Science, Artificial Intelligence
; Computer Science, Interdisciplinary Applications
; Engineering, Biomedical
; Radiology, Nuclear Medicine & Medical Imaging
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WOS记录号 | WOS:000579512600005
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出版者 | |
EI入藏号 | 20203709152766
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EI主题词 | Ophthalmology
; Optical tomography
; Diagnosis
; Medical imaging
; Image analysis
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EI分类号 | Biomedical Engineering:461.1
; Medicine and Pharmacology:461.6
; Data Processing and Image Processing:723.2
; Optical Devices and Systems:741.3
; Imaging Techniques:746
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ESI学科分类 | COMPUTER SCIENCE
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Scopus记录号 | 2-s2.0-85090288812
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:36
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成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/184673 |
专题 | 南方科技大学 工学院_计算机科学与工程系 |
作者单位 | 1.State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou 510060,China 2.Inception Institute of Artificial Intelligence,Abu Dhabi,United Arab Emirates 3.Intelligent Healthcare Unit,Baidu, Beijing,China 4.School of Computer Science and Engineering,South China University of Technology,Guangzhou, Guangdong,China 5.National Scientific and Technical Research Council,CONICET,Argentina 6.Yatiris Group,PLADEMA Institute,Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN),Tandil,Argentina 7.School of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou,China 8.Tencent Jarvis Lab,Shenzhen,China 9.School of Software Engineering,South China University of Technology,Guangzhou,China 10.School of Biomedical Engineering,Health Science Center,Shenzhen University,Shenzhen,China 11.School of Electronic and Information Engineering,Shenzhen University,Shenzhen,China 12.Department of Computer Science and Engineering,The Chinese University of Hong Kong,China 13.School of Electronic and Information Engineering,Soochow University,Suzhou,China 14.Ningbo University,Zhejiang,China 15.Ningbo Institute of Industrial Technology,Chinese Academy of Sciences,Zhejiang,China 16.Southern University of Science and Technology,Shenzhen,China 17.Shanghai Jiaotong University,Shanghai,China 18.Laboratory for Ophthalmic Image Analysis,Department of Ophthalmology,Medical University of Vienna,Vienna,Austria |
推荐引用方式 GB/T 7714 |
Fu,Huazhu,Li,Fei,Sun,Xu,et al. AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography[J]. MEDICAL IMAGE ANALYSIS,2020,66.
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APA |
Fu,Huazhu.,Li,Fei.,Sun,Xu.,Cao,Xingxing.,Liao,Jingan.,...&Xu,Yanwu.(2020).AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography.MEDICAL IMAGE ANALYSIS,66.
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MLA |
Fu,Huazhu,et al."AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography".MEDICAL IMAGE ANALYSIS 66(2020).
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条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | 操作 | |
AGE Challenge Angle (6108KB) | -- | -- | 限制开放 | -- |
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