A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography

PURPOSE: The purpose of this study was to develop and validate a deep learning (DL) framework for the detection and quantification of reticular pseudodrusen (RPD) and drusen on optical coherence tomography (OCT) scans. METHODS: A DL framework was developed consisting of a classification model and an...

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Detalles Bibliográficos
Autores principales: Schwartz, Roy, Khalid, Hagar, Liakopoulos, Sandra, Ouyang, Yanling, de Vente, Coen, González-Gonzalo, Cristina, Lee, Aaron Y., Guymer, Robyn, Chew, Emily Y., Egan, Catherine, Wu, Zhichao, Kumar, Himeesh, Farrington, Joseph, Müller, Philipp L., Sánchez, Clara I., Tufail, Adnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728496/
https://www.ncbi.nlm.nih.gov/pubmed/36458946
http://dx.doi.org/10.1167/tvst.11.12.3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728496/
https://www.ncbi.nlm.nih.gov/pubmed/36458946
http://dx.doi.org/10.1167/tvst.11.12.3

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