AIMC Topic: Tomography, Optical Coherence
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Deep Learning Model for the Detection of Corneal Edema Before Descemet Membrane Endothelial Keratoplasty on Optical Coherence Tomography Images.
Translational vision science & technology
Dec 1, 2022
PURPOSE: Descemet membrane endothelial keratoplasty (DMEK) is the preferred method for treating corneal endothelial dysfunction, such as Fuchs endothelial corneal dystrophy (FECD). The surgical indication is based on the patients' symptoms and the pr...
A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography.
Translational vision science & technology
Dec 1, 2022
PURPOSE: The purpose of this study was to develop and validate a deep learning (DL) framework for the detection and quantification of reticular pseudodrusen (RPD) and drusen on optical coherence tomography (OCT) scans.
Enhanced Diagnosis of Plaque Erosion by Deep Learning in Patients With Acute Coronary Syndromes.
JACC. Cardiovascular interventions
Oct 24, 2022
BACKGROUND: Acute coronary syndromes caused by plaque erosion might be potentially managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires expertise in optical coherence tomographic (OCT) image interpretation. In ...
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).
Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.
Journal of biomedical optics
Oct 1, 2022
SIGNIFICANCE: Coronary heart disease has the highest rate of death and morbidity in the Western world. Atherosclerosis is an asymptomatic condition that is considered the primary cause of cardiovascular diseases. The accumulation of low-density lipop...
Evaluation of Generative Adversarial Networks for High-Resolution Synthetic Image Generation of Circumpapillary Optical Coherence Tomography Images for Glaucoma.
JAMA ophthalmology
Oct 1, 2022
IMPORTANCE: Deep learning (DL) networks require large data sets for training, which can be challenging to collect clinically. Generative models could be used to generate large numbers of synthetic optical coherence tomography (OCT) images to train su...
Etiology of Macular Edema Defined by Deep Learning in Optical Coherence Tomography Scans.
Translational vision science & technology
Sep 1, 2022
PURPOSE: To develop an automated method based on deep learning (DL) to classify macular edema (ME) from the evaluation of optical coherence tomography (OCT) scans.
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.
Pointwise Visual Field Estimation From Optical Coherence Tomography in Glaucoma Using Deep Learning.
Translational vision science & technology
Aug 1, 2022
PURPOSE: Standard automated perimetry is the gold standard to monitor visual field (VF) loss in glaucoma management, but it is prone to intrasubject variability. We trained and validated a customized deep learning (DL) regression model with Xception ...
DEEP LEARNING-BASED PREDICTION OF OUTCOMES FOLLOWING NONCOMPLICATED EPIRETINAL MEMBRANE SURGERY.
Retina (Philadelphia, Pa.)
Aug 1, 2022
PURPOSE: We used deep learning to predict the final central foveal thickness (CFT), changes in CFT, final best corrected visual acuity, and best corrected visual acuity changes following noncomplicated idiopathic epiretinal membrane surgery.
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