Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images

OBJECTIVE: In order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians’ workload. METHOD...

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Detalles Bibliográficos
Autores principales: Yan, Yulin, Jiang, Weiyan, Zhou, Yiwen, Yu, Yi, Huang, Linying, Wan, Shanshan, Zheng, Hongmei, Tian, Miao, Wu, Huiling, Huang, Li, Wu, Lianlian, Cheng, Simin, Gao, Yuelan, Mao, Jiewen, Wang, Yujin, Cong, Yuyu, Deng, Qian, Shi, Xiaoshuo, Yang, Zixian, Miao, Qingmei, Zheng, Biqing, Wang, Yujing, Yang, Yanning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157182/
https://www.ncbi.nlm.nih.gov/pubmed/37153082
http://dx.doi.org/10.3389/fmed.2023.1164188

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157182/
https://www.ncbi.nlm.nih.gov/pubmed/37153082
http://dx.doi.org/10.3389/fmed.2023.1164188

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