Predicting the central 10 degrees visual field in glaucoma by applying a deep learning algorithm to optical coherence tomography images

We aimed to develop a model to predict visual field (VF) in the central 10 degrees in patients with glaucoma, by training a convolutional neural network (CNN) with optical coherence tomography (OCT) images and adjusting the values with Humphrey Field Analyzer (HFA) 24–2 test. The training dataset in...

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Detalles Bibliográficos
Autores principales: Asano, Shotaro, Asaoka, Ryo, Murata, Hiroshi, Hashimoto, Yohei, Miki, Atsuya, Mori, Kazuhiko, Ikeda, Yoko, Kanamoto, Takashi, Yamagami, Junkichi, Inoue, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838164/
https://www.ncbi.nlm.nih.gov/pubmed/33500462
http://dx.doi.org/10.1038/s41598-020-79494-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7838164/
https://www.ncbi.nlm.nih.gov/pubmed/33500462
http://dx.doi.org/10.1038/s41598-020-79494-6

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