Original ArticleA Deep Learning Network for Classifying Arteries and Veins in Montaged Widefield OCT Angiograms
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Supplemental material available at www.ophthalmologyscience.org.
Training Parameters are available at https://github.com/octangio/CAVnet.
Disclosure(s): All authors have completed and submitted the ICMJE disclosures form.
The author(s) have made the following disclosure(s): D.H.: Funding, Consulting, Patent – Optovue; Y.J.: Funding and Patent – Optovue; Patents – Optos. Oregon Health & Science University, Y.J. and D.H. have a financial interest in Optovue, Inc., a company that may have a commercial interest in the results of this research and technology. These potential conflicts of interest have been reviewed and are managed by OHSU.
Funding: National Institutes of Health (R01 EY027833, R01 EY024544, R01 EY031394, P30 EY010572, T32 EY023211); unrestricted departmental funding grant and William & Mary Greve Special Scholar Award from Research to Prevent Blindness (New York, NY); Bright Focus Foundation (G2020168).
HUMAN SUBJECTS: Human subjects were included in this study. The human ethics committees at the Oregon Health & Science University approved the study. All research adhered to the tenets of the Declaration of Helsinki. All participants provided informed consent.
No animal subjects were used in this study.
Author Contributions:
Conception and design: Gao, Jia
Data collection: Gao, Guo, Tsuboi, Pacheco, Poole
Analysis and interpretation: Gao, Guo, Hormel
Obtained funding: Jia, Hwang; Study was performed as part of regular employment duties at Oregon Health & Science University. No additional funding was provided.
Overall responsibility: Gao, Hormel, Bailey, Flaxel, Huang, Hwang, Jia