Individualized Estimation of Baseline Retinal Nerve Fiber Layer Thickness Using Conditional Variational Autoencoder

Individualized Estimation of Baseline Retinal Nerve Fiber Layer Thickness Using Conditional Variational Autoencoder

Purpose: Use generative deep learning (DL) models to estimate baseline reference nerve fiber layer thickness (NFLT) profiles, taking into account individual ocular characteristics. Design: A cross-sectional study. Participants: Six hundred eighty-six individuals from the Hong Kong FAMILY cohort and...

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Main Authors: Ou Tan, PhD, Keke Liu, MD, Aiyin Chen, MD, Dongseok Choi, PhD, Jonathan C.H. Chan, MD, Bonnie N.K. Choy, MD, Kendrick C. Shih, MD, Jasper K.W. Wong, MD, Alex L.K. Ng, MD, Janice J.C. Cheung, MD, Michael Y. Ni, MD, Jimmy S.M. Lai, MD, Gabriel M. Leung, MD, Ian Y.H. Wong, MD, David Huang, MD, PhD
Format: Article
Language:English
Published: Elsevier 2025-11-01
Series:Ophthalmology Science
Subjects:
Conditional variational autoencoder
Glaucoma
Nerve fiber layer thickness
OCT
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914525001472
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