Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism

Significance: Automatic and accurate classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images is essential for assisting ophthalmologist in the diagnosis and grading of macular diseases. Therefore, more effective OCT volume classification for automatic recognition...

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Detalles Bibliográficos
Autores principales: Sun, Yankui, Zhang, Haoran, Yao, Xianlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2020
Materias:
Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493033/
https://www.ncbi.nlm.nih.gov/pubmed/32940026
http://dx.doi.org/10.1117/1.JBO.25.9.096004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493033/
https://www.ncbi.nlm.nih.gov/pubmed/32940026
http://dx.doi.org/10.1117/1.JBO.25.9.096004

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