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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...
Salvato in:
| Pubblicato in: | PLoS One |
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| Autori principali: | , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2019
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| Soggetti: | |
| Accesso online: | 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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