Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images

PURPOSE: To develop a new intelligent system based on deep learning for automatically optical coherence tomography (OCT) images categorization. METHODS: A total of 60,407 OCT images were labeled by 17 licensed retinal experts and 25,134 images were included. One hundred one-layer convolutional neura...

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Detalles Bibliográficos
Autores principales: Lu, Wei, Tong, Yan, Yu, Yue, Xing, Yiqiao, Chen, Changzheng, Shen, Yin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2018
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314222/
https://www.ncbi.nlm.nih.gov/pubmed/30619661
http://dx.doi.org/10.1167/tvst.7.6.41

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314222/
https://www.ncbi.nlm.nih.gov/pubmed/30619661
http://dx.doi.org/10.1167/tvst.7.6.41

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