Predicting the central 10 degrees visual field in glaucoma by applying a deep learning algorithm to optical coherence tomography images
Abstract 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 d...
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/fe4bdf1312fc4483a90537b7a7d8d096 |
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