AIMC Topic: Retinal Ganglion Cells

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Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques.

PloS one May 6, 2019
OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the ...
Middle Aged Image Processing, Computer-Assisted Tomography, Optical Coherence Early Diagnosis Retinal Ganglion Cells Macula Lutea Multiple Sclerosis, Relapsing-Remitting Machine Learning Female Adult Cross-Sectional Studies Male Humans
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A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.

American journal of ophthalmology Jan 26, 2019
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...
Male Middle Aged Deep Learning Vision Disorders Area Under Curve Female Aged Aged, 80 and over Cross-Sectional Studies Intraocular Pressure Visual Field Tests Optic Nerve Diseases Photography Glaucoma, Open-Angle Bruch Membrane Tomography, Optical Coherence Nerve Fibers Optic Disk Retinal Ganglion Cells Visual Fields Humans Algorithms Retrospective Studies
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From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.

Ophthalmology Dec 20, 2018
PURPOSE: Previous approaches using deep learning (DL) algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference training set. We propose a new approach using quantitative s...
Humans Glaucoma, Open-Angle Visual Acuity Tonometry, Ocular Retinal Ganglion Cells Intraocular Pressure Algorithms Tomography, Optical Coherence Gonioscopy Visual Fields Male Fundus Oculi Female Visual Field Tests Middle Aged Nerve Fibers Aged Optic Nerve Diseases Deep Learning Optic Disk Aged, 80 and over Photography ROC Curve Cross-Sectional Studies
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Using Deep Learning and Transfer Learning to Accurately Diagnose Early-Onset Glaucoma From Macular Optical Coherence Tomography Images.

American journal of ophthalmology Oct 12, 2018
PURPOSE: We sought to construct and evaluate a deep learning (DL) model to diagnose early glaucoma from spectral-domain optical coherence tomography (OCT) images.
Tomography, Optical Coherence Datasets as Topic Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Transfer, Psychology Glaucoma, Open-Angle Humans Gonioscopy Glaucoma Male Female Middle Aged Reproducibility of Results Deep Learning Aged ROC Curve Adult Area Under Curve Sensitivity and Specificity Intraocular Pressure
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Efficient coding matters in the organization of the early visual system.

Neural networks : the official journal of the International Neural Network Society May 16, 2018
Individual areas in the brain are organized into a hierarchical network as a result of evolution. Previous work indicated that the receptive fields (RFs) of individual areas have been evolved to favor metabolically efficient neural codes. In this pap...
Visual Cortex Humans Neural Networks, Computer Visual Pathways Models, Neurological Retinal Ganglion Cells Visual Perception
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Evaluation of CNTNAP2 gene rs2107856 polymorphism in Turkish population with pseudoexfoliation syndrome.

International ophthalmology Dec 19, 2017
PURPOSE: To investigate rs2107856 single-nucleotide polymorphism (SNP) of CNTNAP2 gene in Turkish population with pseudoexfoliation and to correlate clinical characteristics with the genotypic profile.
Polymorphism, Genetic Incidence Exfoliation Syndrome Aged, 80 and over Humans Genotype Cross-Sectional Studies Prospective Studies Membrane Proteins Tomography, Optical Coherence Intraocular Pressure Female Nerve Tissue Proteins DNA Male Aged Visual Acuity Turkey Middle Aged Retinal Ganglion Cells Polymerase Chain Reaction
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Letter identification and the neural image classifier.

Journal of vision Feb 12, 2015
Letter identification is an important visual task for both practical and theoretical reasons. To extend and test existing models, we have reviewed published data for contrast sensitivity for letter identification as a function of size and have also c...
Retinal Ganglion Cells Classification Models, Psychological Pattern Recognition, Visual Contrast Sensitivity Humans Neural Networks, Computer Retina
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Multimodal Artificial Intelligence Models Predicting Glaucoma Progression Using Electronic Health Records and Retinal Nerve Fiber Layer Scans.

Translational vision science & technology Mar 3, 2025
PURPOSE: The purpose of this study was to develop models that predict which patients with glaucoma will progress to require surgery, combining structured data from electronic health records (EHRs) and retinal fiber layer optical coherence tomography ...
Humans Glaucoma Artificial Intelligence Retrospective Studies Electronic Health Records Deep Learning Female ROC Curve Aged Tomography, Optical Coherence Male Nerve Fibers Middle Aged Retinal Ganglion Cells Disease Progression
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RetOCTNet: Deep Learning-Based Segmentation of OCT Images Following Retinal Ganglion Cell Injury.

Translational vision science & technology Feb 3, 2025
PURPOSE: We present RetOCTNet, a deep learning tool to segment the retinal nerve fiber layer (RNFL) and total retinal thickness automatically from optical coherence tomography (OCT) scans in rats following retinal ganglion cell (RGC) injury.
Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Ocular Hypertension Optic Nerve Injuries Animals Male Deep Learning Rats Disease Models, Animal
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Explainable Deep Learning for Glaucomatous Visual Field Prediction: Artifact Correction Enhances Transformer Models.

Translational vision science & technology Jan 2, 2025
PURPOSE: The purpose of this study was to develop a deep learning approach that restores artifact-laden optical coherence tomography (OCT) scans and predicts functional loss on the 24-2 Humphrey Visual Field (HVF) test.
Tomography, Optical Coherence Artifacts Retinal Ganglion Cells Visual Fields Visual Field Tests Humans Aged Neural Networks, Computer Cross-Sectional Studies Male Glaucoma Middle Aged Deep Learning Retrospective Studies Female
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