AIMC Topic: Tomography, Optical Coherence
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Visual Field Inference From Optical Coherence Tomography Using Deep Learning Algorithms: A Comparison Between Devices.
Translational vision science & technology
Jun 1, 2021
PURPOSE: To develop a deep learning model to estimate the visual field (VF) from spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) and to compare the performance between them.
INTERMEDIATE AND DEEP CAPILLARY PLEXUSES IN MACHINE LEARNING SEGMENTATION OF HIGH-RESOLUTION OPTICAL COHERENCE TOMOGRAPHY IMAGING.
Retina (Philadelphia, Pa.)
Jun 1, 2021
PURPOSE: To describe imaging produced by machine learning-based segmentation of high-resolution optical coherence tomography imaging of the intermediate capillary plexus and deep capillary plexus, layers of vessels not imaged well by dye-based angiog...
ANALYSIS OF FLUID VOLUME AND ITS IMPACT ON VISUAL ACUITY IN THE FLUID STUDY AS QUANTIFIED WITH DEEP LEARNING.
Retina (Philadelphia, Pa.)
Jun 1, 2021
PURPOSE: To investigate quantitative differences in fluid volumes between subretinal fluid (SRF)-tolerant and SRF-intolerant treat-and-extend regimens for neovascular age-related macular degeneration and analyze the association with best-corrected vi...
Double-path parallel convolutional neural network for removing speckle noise in different types of OCT images.
Applied optics
May 20, 2021
Speckle noises widely exist in optical coherence tomography (OCT) images. We propose an improved double-path parallel convolutional neural network (called DPNet) to reduce speckles. We increase the network width to replace the network depth to extrac...
Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization.
Translational vision science & technology
May 3, 2021
PURPOSE: The purpose of this study was to evaluate the predictive value of optical coherence tomography (OCT) and OCT angiography (OCTA) parameters at baseline on lesion's activity at the 1-year follow-up in type 1 macular neovascularizations (MNVs) ...
Automatic Anterior Chamber Angle Classification Using Deep Learning System and Anterior Segment Optical Coherence Tomography Images.
Translational vision science & technology
May 3, 2021
PURPOSE: The purpose of this study was to develop a software package for the automatic classification of anterior chamber angle using anterior segment optical coherence tomography (AS-OCT).
DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.
Retina (Philadelphia, Pa.)
May 1, 2021
PURPOSE: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images.
Automatic Segmentation in Multiple OCT Layers For Stargardt Disease Characterization Via Deep Learning.
Translational vision science & technology
Apr 1, 2021
PURPOSE: This study sought to perform automated segmentation of 11 retinal layers and Stargardt-associated features on spectral-domain optical coherence tomography (SD-OCT) images and to analyze differences between normal eyes and eyes diagnosed with...
Strategies to Improve Convolutional Neural Network Generalizability and Reference Standards for Glaucoma Detection From OCT Scans.
Translational vision science & technology
Apr 1, 2021
PURPOSE: To develop and evaluate methods to improve the generalizability of convolutional neural networks (CNNs) trained to detect glaucoma from optical coherence tomography retinal nerve fiber layer probability maps, as well as optical coherence tom...
Artificial intelligence and complex statistical modeling in glaucoma diagnosis and management.
Current opinion in ophthalmology
Mar 1, 2021
PURPOSE OF REVIEW: The field of artificial intelligence has grown exponentially in recent years with new technology, methods, and applications emerging at a rapid rate. Many of these advancements have been used to improve the diagnosis and management...
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