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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Vydáno v:Transl Vis Sci Technol
Hlavní autoři: Le, David, Alam, Minhaj, Yao, Cham K., Lim, Jennifer I., Hsieh, Yi-Ting, Chan, Robison V. P., Toslak, Devrim, Yao, Xincheng
Médium: Artigo
Jazyk:Inglês
Vydáno: The Association for Research in Vision and Ophthalmology 2020
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On-line přístup: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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