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

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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Bibliographic Details
Main Authors: Andreas Maunz, Fethallah Benmansour, Yvonna Li, Thomas Albrecht, Yan-Ping Zhang, Filippo Arcadu, Yalin Zheng, Savita Madhusudhan, Jayashree Sahni
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Journal of Personalized Medicine
Subjects:
age-related macular degeneration
choroidal neovascularization
classification
machine learning
optical coherence tomography
Online Access:https://www.mdpi.com/2075-4426/11/6/524

Internet

https://www.mdpi.com/2075-4426/11/6/524

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