Semi-supervised generative adversarial networks for closed-angle detection on anterior segment optical coherence tomography images: an empirical study with a small training dataset

BACKGROUND: Semi-supervised learning algorithms can leverage an unlabeled dataset when labeling is limited or expensive to obtain. In the current study, we developed and evaluated a semi-supervised generative adversarial networks (GANs) model that detects closed-angle on anterior segment optical coh...

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Detalles Bibliográficos
Autores principales: Zheng, Ce, Koh, Victor, Bian, Fang, Li, Luo, Xie, Xiaolin, Wang, Zilei, Yang, Jianlong, Chew, Paul Tec Kuan, Zhang, Mingzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339863/
https://www.ncbi.nlm.nih.gov/pubmed/34422985
http://dx.doi.org/10.21037/atm-20-7436

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339863/
https://www.ncbi.nlm.nih.gov/pubmed/34422985
http://dx.doi.org/10.21037/atm-20-7436

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