PURPOSE: To develop and train a deep learning-based algorithm for detecting disorganization of retinal inner layers (DRIL) on optical coherence tomography (OCT) to screen a cohort of patients with diabetic retinopathy (DR).
PURPOSE: To diagnose and segment choroidal neovascularization (CNV) in a real-world multicenter clinical OCT angiography (OCTA) data set using deep learning.
IMPORTANCE: There is no widespread effective treatment to halt the progression of retinitis pigmentosa. Consequently, adequate assessment and estimation of residual visual function are important clinically.
Translational vision science & technology
Mar 2, 2022
PURPOSE: The purpose of this study was to design an automated algorithm that can detect fluorescence leakage accurately and quickly without the use of a large amount of labeled data.
Translational vision science & technology
Feb 1, 2022
PURPOSE: To develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolutional neural network (CNN) and to verify the feasibility of the system.
Translational vision science & technology
Feb 1, 2022
PURPOSE: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.
PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.
Translational vision science & technology
Nov 1, 2021
PURPOSE: We propose a deep learning-based image reconstruction algorithm to produce high-resolution optical coherence tomographic angiograms (OCTA) of the intermediate capillary plexus (ICP) and deep capillary plexus (DCP).
PURPOSE: To investigate associations between residual subretinal fluid (rSRF) volumes, quantified using artificial intelligence and treatment outcomes in a subretinal fluid (SRF)-tolerant treat-and-extend (T&E) regimen in neovascular age-related macu...
PURPOSE OF REVIEW: Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence ...
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