AIMC Topic: Choroid
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Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.
Translational vision science & technology
Apr 2, 2024
PURPOSE: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and diagnostic markers.
An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.
Translational vision science & technology
Nov 1, 2023
PURPOSE: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data.
A Deep Learning-Based Fully Automated Program for Choroidal Structure Analysis Within the Region of Interest in Myopic Children.
Translational vision science & technology
Mar 1, 2023
PURPOSE: To develop and validate a fully automated program for choroidal structure analysis within a 1500-µm-wide region of interest centered on the fovea (deep learning-based choroidal structure assessment program [DCAP]).
Application of Deep Learning for Automated Detection of Polypoidal Choroidal Vasculopathy in Spectral Domain Optical Coherence Tomography.
Translational vision science & technology
Oct 3, 2022
OBJECTIVE: To develop an automated polypoidal choroidal vasculopathy (PCV) screening model to distinguish PCV from wet age-related macular degeneration (wet AMD).
Feasibility of Automated Segmentation of Pigmented Choroidal Lesions in OCT Data With Deep Learning.
Translational vision science & technology
Sep 1, 2022
PURPOSE: To evaluate the feasibility of automated segmentation of pigmented choroidal lesions (PCLs) in optical coherence tomography (OCT) data and compare the performance of different deep neural networks.
DENOISING SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY VOLUMETRIC SCANS USING A DEEP LEARNING MODEL.
Retina (Philadelphia, Pa.)
Mar 1, 2022
PURPOSE: To evaluate the use of a deep learning noise reduction model on swept source optical coherence tomography volumetric scans.
Application of Artificial Intelligence and Deep Learning for Choroid Segmentation in Myopia.
Translational vision science & technology
Feb 1, 2022
PURPOSE: To investigate the correlation between choroidal thickness and myopia progression using a deep learning method.
Application of Deep Learning Methods for Binarization of the Choroid in Optical Coherence Tomography Images.
Translational vision science & technology
Feb 1, 2022
PURPOSE: The purpose of this study was to develop a deep learning model for automatic binarization of the choroidal tissue, separating choroidal blood vessels from nonvascular stromal tissue, in optical coherence tomography (OCT) images from healthy ...
Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning.
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.
Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning.
Translational vision science & technology
Nov 1, 2021
PURPOSE: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalen...
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