Automated choroidal neovascularization diagnosis and quantification using convolutional neural networks in OCT angiography (Conference Presentation)

Jie Wang; Tristan Hormel; Liqin Gao; Pengxiao Zang; Yukun Guo; Steven T. Bailey; Yali Jia

doi:10.1117/12.2544490

9 March 2020 Automated choroidal neovascularization diagnosis and quantification using convolutional neural networks in OCT angiography (Conference Presentation)

Jie Wang, Tristan Hormel, Liqin Gao, Pengxiao Zang, Yukun Guo, Steven T. Bailey, Yali Jia

Author Affiliations +

Proceedings Volume 11218, Ophthalmic Technologies XXX; 1121809 (2020) https://doi.org/10.1117/12.2544490
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Detecting and quantifying choroidal neovascularization (CNV) is essential for the diagnosis of neovascular age-related macular degeneration (AMD). Projection-resolved OCT angiography (PR-OCTA) has enabled both en face and volumetric visualization of CNV. However, previously described CNV detection methods only quantify CNV that was already diagnosed, and were unable to identify CNV form unknown inputs . Previous methods were also limited by artifacts. A fully automated CNV diagnosis and quantification algorithm using convolutional neural networks (CNNs) was developed. It was able to diagnose CNV and output CNV membrane and vessel area from retinal structural and angiographic images.

Conference Presentation

Citation Download Citation

Jie Wang, Tristan Hormel, Liqin Gao, Pengxiao Zang, Yukun Guo, Steven T. Bailey, and Yali Jia "Automated choroidal neovascularization diagnosis and quantification using convolutional neural networks in OCT angiography (Conference Presentation)", Proc. SPIE 11218, Ophthalmic Technologies XXX, 1121809 (9 March 2020); https://doi.org/10.1117/12.2544490

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