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.

Date Published: 9 March 2020
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Proc. SPIE 11218, Ophthalmic Technologies XXX, 1121809 (9 March 2020); doi: 10.1117/12.2544490

Published in SPIE Proceedings Vol. 11218:
Ophthalmic Technologies XXX
Fabrice Manns; Arthur Ho; Per G. Söderberg, Editor(s)