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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Detalles Bibliográficos
Autores principales: Nagasato, Daisuke, Tabuchi, Hitoshi, Masumoto, Hiroki, Enno, Hiroki, Ishitobi, Naofumi, Kameoka, Masahiro, Niki, Masanori, Mitamura, Yoshinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6837754/
https://www.ncbi.nlm.nih.gov/pubmed/31697697
http://dx.doi.org/10.1371/journal.pone.0223965

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6837754/
https://www.ncbi.nlm.nih.gov/pubmed/31697697
http://dx.doi.org/10.1371/journal.pone.0223965

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