Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD

Background: The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD). Methods: Used in DL model training and testing were 341 subjects with no...

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Detalles Bibliográficos
Autores principales: Kalra, Gagan, Cetin, Hasan, Whitney, Jon, Yordi, Sari, Cakir, Yavuz, McConville, Conor, Whitmore, Victoria, Bonnay, Michelle, Reese, Jamie L., Srivastava, Sunil K., Ehlers, Justis P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047385/
https://www.ncbi.nlm.nih.gov/pubmed/36980486
http://dx.doi.org/10.3390/diagnostics13061178

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047385/
https://www.ncbi.nlm.nih.gov/pubmed/36980486
http://dx.doi.org/10.3390/diagnostics13061178

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