A Deep Learning Network for Classifying Arteries and Veins in Montaged Widefield OCT Angiograms

PURPOSE: To propose a deep-learning−based method to differentiate arteries from veins in montaged widefield OCT angiography (OCTA). DESIGN: Cross-sectional study. PARTICIPANTS: A total of 232 participants, including 109 participants with diabetic retinopathy (DR), 64 participants with branch retinal...

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Detalles Bibliográficos
Autores principales: Gao, Min, Guo, Yukun, Hormel, Tristan T., Tsuboi, Kotaro, Pacheco, George, Poole, David, Bailey, Steven T., Flaxel, Christina J., Huang, David, Hwang, Thomas S., Jia, Yali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562370/
https://www.ncbi.nlm.nih.gov/pubmed/36278031
http://dx.doi.org/10.1016/j.xops.2022.100149

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562370/
https://www.ncbi.nlm.nih.gov/pubmed/36278031
http://dx.doi.org/10.1016/j.xops.2022.100149

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