Peer-Reviewed Publication
Med Image Anal2026;112104128.July 1, 2026Journal Article
STAGE challenge: Structural-Functional Transition in Glaucoma Assessment.
Shiqi Zhou1, Yuancong Liang1, Huihui Fang2, Di Liu3, Li Wei3, Ziyang Chen4, Yong Xia4, Chubin Ou5, Yihao Li6, Yubo Tan7, Bo Yang3, Haojie Yin8, Chengcheng Feng9, Hao Zhou10, Hrvoje Bogunović11, Huazhu Fu12, Fei Li13, Xiulan Zhang14, Yanwu Xu15
1School of Future Technology, South China University of Technology, Guangzhou, China; Pazhou Lab, Guangzhou, China.
2Pazhou Lab, Guangzhou, China. Electronic address: fanghuihuibit@163.com.
3AIFUTURE Lab, Beijing, China.
4Northwestern Polytechnical University, Xi'an, China.
5Guangdong Weiren Meditech Co Ltd, Foshan, China.
6LaTIM UMR 1101, Inserm, Brest, France; University of Western Brittany, Brest, France.
7University of Electronic Science and Technology of China, Chengdu, China.
8Institute of Automation, Chinese Academy of Sciences, Beijing, China.
9Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
10Sun Yat-sen University, Guangzhou, China.
11Medical University of Vienna, Vienna, Austria.
12Institute of High Performance Computing, A*STAR, Singapore, Singapore.
13State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China. Electronic address: lifei57@mail.sysu.edu.cn.
14State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China. Electronic address: zhangxl2@mail.sysu.edu.cn.
15School of Future Technology, South China University of Technology, Guangzhou, China; Pazhou Lab, Guangzhou, China. Electronic address: ywxu@ieee.org.
Abstract
Glaucoma is a leading cause of irreversible yet preventable blindness in working-age populations. Clinical diagnos is currently relies on functional visual field (VF) examinations to evaluate visual function and monitor disease progression, but these tests are time-consuming and require close cooperation with ophthalmologists, limiting their practicality. Although deep learning has shown promise f…
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