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Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography
PURPOSE: The present study aimed to compare the accuracy of diabetic retinopathy (DR) staging with a deep convolutional neural network (DCNN) using two different types of fundus cameras and composite images. METHOD: The study included 491 ultra-wide-field fundus ophthalmoscopy and optical coherence...
Autores principales: | Nagasawa, Toshihiko, Tabuchi, Hitoshi, Masumoto, Hiroki, Morita, Shoji, Niki, Masanori, Ohara, Zaigen, Yoshizumi, Yuki, Mitamura, Yoshinori |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041547/ https://www.ncbi.nlm.nih.gov/pubmed/33884202 http://dx.doi.org/10.1155/2021/6651175 |
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