Automated detection of a nonperfusion area caused by retinal vein occlusion in optical coherence tomography angiography images using deep learning

We aimed to assess the ability of deep learning (DL) and support vector machine (SVM) to detect a nonperfusion area (NPA) caused by retinal vein occlusion (RVO) with optical coherence tomography angiography (OCTA) images. The study included 322 OCTA images (normal: 148; NPA owing to RVO: 174 [128 br...

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Udgivet i:PLoS One
Main Authors: Nagasato, Daisuke, Tabuchi, Hitoshi, Masumoto, Hiroki, Enno, Hiroki, Ishitobi, Naofumi, Kameoka, Masahiro, Niki, Masanori, Mitamura, Yoshinori
Format: Artigo
Sprog:Inglês
Udgivet: Public Library of Science 2019
Fag:
Research Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6837754/
https://ncbi.nlm.nih.gov/pubmed/31697697
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0223965
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