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Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy
PURPOSE: To test the feasibility of using deep learning for optical coherence tomography angiography (OCTA) detection of diabetic retinopathy. METHODS: A deep-learning convolutional neural network (CNN) architecture, VGG16, was employed for this study. A transfer learning process was implemented to...
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| Publicado no: | Transl Vis Sci Technol |
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| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
The Association for Research in Vision and Ophthalmology
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7424949/ https://ncbi.nlm.nih.gov/pubmed/32855839 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.9.2.35 |
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