Accuracy of a Machine-Learning Algorithm for Detecting and Classifying Choroidal Neovascularization on Spectral-Domain Optical Coherence Tomography

Background: To evaluate the performance of a machine-learning (ML) algorithm to detect and classify choroidal neovascularization (CNV), secondary to age-related macular degeneration (AMD) on spectral-domain optical coherence tomography (SD-OCT) images. Methods: Baseline fluorescein angiography (FA)...

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Detalles Bibliográficos
Autores principales: Maunz, Andreas, Benmansour, Fethallah, Li, Yvonna, Albrecht, Thomas, Zhang, Yan-Ping, Arcadu, Filippo, Zheng, Yalin, Madhusudhan, Savita, Sahni, Jayashree
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227725/
https://www.ncbi.nlm.nih.gov/pubmed/34201045
http://dx.doi.org/10.3390/jpm11060524

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227725/
https://www.ncbi.nlm.nih.gov/pubmed/34201045
http://dx.doi.org/10.3390/jpm11060524

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