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Optica, Biomedical Optics Express, 9(6), p. 3564, 2015

DOI: 10.1364/boe.6.003564

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Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography

Journal article published in 2015 by Li Liu, Simon S. Gao ORCID, Steven T. Bailey ORCID, David Huang, Dengwang Li, Yali Jia
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.