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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Detalles Bibliográficos
Autores principales: Chen, Henry Shen-Lih, Chen, Guan-An, Syu, Jhen-Yang, Chuang, Lan-Hsin, Su, Wei-Wen, Wu, Wei-Chi, Liu, Jian-Hong, Chen, Jian-Ren, Huang, Su-Chen, Kang, Eugene Yu-Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Artificial Intelligence and Big Data
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559108/
https://www.ncbi.nlm.nih.gov/pubmed/36245759
http://dx.doi.org/10.1016/j.xops.2022.100180

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559108/
https://www.ncbi.nlm.nih.gov/pubmed/36245759
http://dx.doi.org/10.1016/j.xops.2022.100180

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