Multiview Volume and Temporal Difference Network for Angle-Closure Glaucoma Screening from AS-OCT Videos

Hao, Luoying1; Hu, Yan1; Higashita, Risa2; Yu, James J. Q.1; Zheng, Ce3; Liu, Jiang1,4,5

2022-04-07

10.1155/2022/2722608

Journal of Healthcare Engineering   影响因子和分区

2040-2295

2040-2309

Background. Precise and comprehensive characterizations from anterior segment optical coherence tomography (AS-OCT) are of great importance in facilitating the diagnosis of angle-closure glaucoma. Existing automated analysis methods focus on analyzing structural properties identified from the single AS-OCT image, which is limited to comprehensively representing the status of the anterior chamber angle (ACA). Dynamic iris changes are evidenced as a risk factor in primary angle-closure glaucoma. Method. In this work, we focus on detecting the ACA status from AS-OCT videos, which are captured in a dark-bright-dark changing environment. We first propose a multiview volume and temporal difference network (MT-net). Our method integrates the spatial structural information from multiple views of AS-OCT videos and utilizes temporal dynamics of iris regions simultaneously based on image difference. Moreover, to reduce the video jitter caused by eye movement, we employ preprocessing to align the corneal part between video frames. The regions of interest (ROIs) in appearance and dynamics are also automatically detected to intensify the related informative features. Results. In this work, we employ two AS-OCT video datasets captured by two different devices to evaluate the performance, which includes a total of 342 AS-OCT videos. For the Casia dataset, the classification accuracy for our MT-net is 0.866 with a sensitivity of 0.857 and a specificity of 0.875, which achieves superior performance compared with the results of the algorithms based on AS-OCT images with an obvious gap. For the Zeiss AS-OCT video dataset, our method also gets better performance against the methods based on AS-OCT images with a classification accuracy of 0.833, a sensitivity of 0.860, and a specificity of 0.800. Conclusions. The AS-OCT videos captured under changing environments can be a comprehended means for angle-closure classification. The effectiveness of our proposed MT-net is proved by two datasets from different manufacturers

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China[8210072776] ; Science and Technology Innovation Committee of Shenzhen City["JCYJ20200109140820699",20200925174052004] ; Guangdong Basic and Applied Basic Research Foundation[2021A1515012195] ; Guangdong Provincial Department of Education[2020ZDZX3043] ; Guangdong Provincial Key Laboratory[2020B121201001]

Health Care Sciences & Services

Health Care Sciences & Services

WOS:000791252500006

HINDAWI LTD

20221812048878

Classification (of information) ; Ophthalmology ; Optical tomography

Medicine and Pharmacology:461.6 ; Information Theory and Signal Processing:716.1 ; Optical Devices and Systems:741.3 ; Information Sources and Analysis:903.1

Web of Science

1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen 518055, Peoples R China
2.Tomey Corp, Nagoya, Aichi 4510051, Japan
3.Shanghai Jiao Tong Univ, Xinhua Hosp, Dept Ophthalmol, Sch Med, Shanghai, Peoples R China
4.Wenzhou Med Univ, Sch Ophthalmol & Optometry, Sch Biomed Engn, Wenzhou, Zhejiang, Peoples R China
5.Southern Univ Sci & Technol, Res Inst Trustworthy Autonomous Syst, Shenzhen 518055, Peoples R China

Hao, Luoying,Hu, Yan,Higashita, Risa,et al. Multiview Volume and Temporal Difference Network for Angle-Closure Glaucoma Screening from AS-OCT Videos[J]. Journal of Healthcare Engineering,2022,2022.

Hao, Luoying,Hu, Yan,Higashita, Risa,Yu, James J. Q.,Zheng, Ce,&Liu, Jiang.(2022).Multiview Volume and Temporal Difference Network for Angle-Closure Glaucoma Screening from AS-OCT Videos.Journal of Healthcare Engineering,2022.

Hao, Luoying,et al."Multiview Volume and Temporal Difference Network for Angle-Closure Glaucoma Screening from AS-OCT Videos".Journal of Healthcare Engineering 2022(2022).