Assessment of Generative Adversarial Networks for Synthetic Anterior Segment Optical Coherence Tomography Images in Closed-Angle Detection

PURPOSE: To develop generative adversarial networks (GANs) that synthesize realistic anterior segment optical coherence tomography (AS-OCT) images and evaluate deep learning (DL) models that are trained on real and synthetic datasets for detecting angle closure. METHODS: The GAN architecture was ado...

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Detalles Bibliográficos
Autores principales: Zheng, Ce, Bian, Fang, Li, Luo, Xie, Xiaolin, Liu, Hui, Liang, Jianheng, Chen, Xu, Wang, Zilei, Qiao, Tong, Yang, Jianlong, Zhang, Mingzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088224/
https://www.ncbi.nlm.nih.gov/pubmed/34004012
http://dx.doi.org/10.1167/tvst.10.4.34

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088224/
https://www.ncbi.nlm.nih.gov/pubmed/34004012
http://dx.doi.org/10.1167/tvst.10.4.34

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