Early Glaucoma Detection by Using Style Transfer to Predict Retinal Nerve Fiber Layer Thickness Distribution on the Fundus Photograph

Early Glaucoma Detection by Using Style Transfer to Predict Retinal Nerve Fiber Layer Thickness Distribution on the Fundus Photograph

Objective: We aimed to develop a deep learning (DL)–based algorithm for early glaucoma detection based on color fundus photographs that provides information on defects in the retinal nerve fiber layer (RNFL) and its thickness from the mapping and translating relations of spectral domain OCT (SD-OCT)...

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Bibliographic Details
Main Authors: Henry Shen-Lih Chen, MD, MBA, Guan-An Chen, MSc, Jhen-Yang Syu, MSc, Lan-Hsin Chuang, MD, Wei-Wen Su, MD, Wei-Chi Wu, MD, PhD, Jian-Hong Liu, MSc, Jian-Ren Chen, PhD, Su-Chen Huang, MSc, Eugene Yu-Chuan Kang, MD
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Ophthalmology Science
Subjects:
Image-to-image translation
Glaucoma
Autoencoder
OCT
Retinal nerve fiber layer thickness
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914522000690

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http://www.sciencedirect.com/science/article/pii/S2666914522000690

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