Deep Learning for Diagnosing and Segmenting Choroidal Neovascularization in OCT Angiography in a Large Real-World Data Set

PURPOSE: To diagnose and segment choroidal neovascularization (CNV) in a real-world multicenter clinical OCT angiography (OCTA) data set using deep learning. METHODS: A total of 105,66 OCTA scans from 3135 eyes, including 4701 with CNV and 5865 without, were collected in five eye clinics. Both 3 × 3...

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Detalles Bibliográficos
Autores principales: Wang, Jie, Hormel, Tristan T., Tsuboi, Kotaro, Wang, Xiaogang, Ding, Xiaoyan, Peng, Xiaoyan, Huang, David, Bailey, Steven T., Jia, Yali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117225/
https://www.ncbi.nlm.nih.gov/pubmed/37058103
http://dx.doi.org/10.1167/tvst.12.4.15

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117225/
https://www.ncbi.nlm.nih.gov/pubmed/37058103
http://dx.doi.org/10.1167/tvst.12.4.15

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