AIMC Topic: Retinal Ganglion Cells

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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.
Intraocular Pressure Male Middle Aged Deep Learning ROC Curve Area Under Curve Tomography, Optical Coherence Datasets as Topic Nerve Fibers Glaucoma, Open-Angle Gonioscopy Reproducibility of Results Retinal Ganglion Cells Aged Visual Fields Adult Visual Field Tests Humans Sensitivity and Specificity Transfer, Psychology Glaucoma Female
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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 Pathways Neural Networks, Computer Models, Neurological Humans Retinal Ganglion Cells Visual Perception Visual Cortex
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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.
Retinal Ganglion Cells Middle Aged Aged, 80 and over Humans Nerve Tissue Proteins Prospective Studies Polymerase Chain Reaction Cross-Sectional Studies Incidence Female Visual Acuity Polymorphism, Genetic Intraocular Pressure Genotype Aged Exfoliation Syndrome Membrane Proteins Male Tomography, Optical Coherence DNA Turkey
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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...
Humans Neural Networks, Computer Retina Retinal Ganglion Cells Models, Psychological Classification Pattern Recognition, Visual Contrast Sensitivity
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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 ...
Glaucoma Artificial Intelligence Retrospective Studies Electronic Health Records Female Humans Deep Learning ROC Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Aged Male Middle Aged 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.
Retinal Ganglion Cells Ocular Hypertension Optic Nerve Injuries Animals Male Deep Learning Rats Disease Models, Animal Tomography, Optical Coherence Nerve Fibers
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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.
Humans Neural Networks, Computer Glaucoma Retrospective Studies Visual Fields Visual Field Tests Middle Aged Deep Learning Tomography, Optical Coherence Artifacts Retinal Ganglion Cells Female Aged Cross-Sectional Studies Male
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CNN-Based Device-Agnostic Feature Extraction From ONH OCT Scans.

Translational vision science & technology Dec 2, 2024
PURPOSE: Optical coherence tomography (OCT)-derived measurements of the optic nerve head (ONH) from different devices are not interchangeable. This poses challenges to patient follow-up and collaborative studies. Here, we present a device-agnostic me...
Neural Networks, Computer Female Aged Adult Male Humans Retinal Ganglion Cells Middle Aged Tomography, Optical Coherence Nerve Fibers Optic Disk
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Using Multi-Layer Perceptron Driven Diagnosis to Compare Biomarkers for Primary Open Angle Glaucoma.

Investigative ophthalmology & visual science Sep 3, 2024
PURPOSE: To use neural network machine learning (ML) models to identify the most relevant ocular biomarkers for the diagnosis of primary open-angle glaucoma (POAG).
Retinal Ganglion Cells Visual Fields Glaucoma, Open-Angle Aged Intraocular Pressure Male Middle Aged ROC Curve Area Under Curve Tomography, Optical Coherence Nerve Fibers Optic Disk Neural Networks, Computer Prospective Studies Biomarkers Female Humans
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Visual Field Prognosis From Macula and Circumpapillary Spectral Domain Optical Coherence Tomography.

Translational vision science & technology Jun 3, 2024
PURPOSE: To explore the structural-functional loss relationship from optic-nerve-head- and macula-centred spectral-domain (SD) Optical Coherence Tomography (OCT) images in the full spectrum of glaucoma patients using deep-learning methods.
Female Visual Fields Aged Visual Field Tests Male Macula Lutea Deep Learning Humans Middle Aged Tomography, Optical Coherence Glaucoma Nerve Fibers Prognosis Optic Disk Retinal Ganglion Cells
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