Deep Learning Approach Predicts Longitudinal Retinal Nerve Fiber Layer Thickness Changes

Deep Learning Approach Predicts Longitudinal Retinal Nerve Fiber Layer Thickness Changes

This study aims to develop deep learning (DL) models to predict the retinal nerve fiber layer (RNFL) thickness changes in glaucoma, facilitating the early diagnosis and monitoring of disease progression. Using the longitudinal data from two glaucoma studies (Diagnostic Innovations in Glaucoma Study...

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Bibliographic Details
Main Authors: Jalil Jalili, Evan Walker, Christopher Bowd, Akram Belghith, Michael H. Goldbaum, Massimo A. Fazio, Christopher A. Girkin, Carlos Gustavo De Moraes, Jeffrey M. Liebmann, Robert N. Weinreb, Linda M. Zangwill, Mark Christopher
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Bioengineering
Subjects:
glaucoma
deep learning
RNFL thickness prediction
optical coherence tomography
one-dimensional convolutional neural network
longitudinal OCT
Online Access:https://www.mdpi.com/2306-5354/12/2/139
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https://www.mdpi.com/2306-5354/12/2/139

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