AIMC Topic: Visual Field Tests

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High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

Translational vision science & technology May 1, 2025
PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis and management. The ability to accurately digitize VF reports is critical for maximizing the utility...
Reproducibility of Results Convolutional Neural Networks Visual Fields Visual Field Tests Humans Neural Networks, Computer Glaucoma
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Structure-Function Correlation of Deep-Learning Quantified Ellipsoid Zone and Retinal Pigment Epithelium Loss and Microperimetry in Geographic Atrophy.

Investigative ophthalmology & visual science Mar 3, 2025
PURPOSE: The purpose of this study was to define structure-function correlation of geographic atrophy (GA) on optical coherence tomography (OCT) and functional testing on microperimetry (MP) based on deep-learning (DL)-quantified spectral-domain OCT ...
Tomography, Optical Coherence Humans Visual Fields Prospective Studies Male Visual Field Tests Female Geographic Atrophy Middle Aged Retinal Pigment Epithelium Aged Deep Learning Aged, 80 and over Visual Acuity
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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 Retinal Ganglion Cells Visual Fields Visual Field Tests Middle Aged Female Deep Learning Aged Tomography, Optical Coherence Cross-Sectional Studies Artifacts Male
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Long-Term Rate of Optic Disc Rim Loss in Glaucoma Patients Measured From Optic Disc Photographs With a Deep Neural Network.

Translational vision science & technology Sep 3, 2024
PURPOSE: This study uses deep neural network-generated rim-to-disc area ratio (RADAR) measurements and the disc damage likelihood scale (DDLS) to measure the rate of optic disc rim loss in a large cohort of glaucoma patients.
Middle Aged Disease Progression ROC Curve Optic Disk Aged Adult Intraocular Pressure Male Visual Fields Visual Field Tests Optic Nerve Diseases Photography Humans Neural Networks, Computer Glaucoma Retrospective Studies Female
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Transformer-Based Deep Learning Prediction of 10-Degree Humphrey Visual Field Tests From 24-Degree Data.

Translational vision science & technology Aug 1, 2024
PURPOSE: To predict 10-2 Humphrey visual fields (VFs) from 24-2 VFs and associated non-total deviation features using deep learning.
Tomography, Optical Coherence Visual Fields Visual Field Tests Male Middle Aged Deep Learning Vision Disorders Glaucoma Female Aged Adult 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.
Tomography, Optical Coherence Aged Visual Fields Nerve Fibers Humans Male Visual Field Tests Optic Disk Glaucoma Middle Aged Macula Lutea Retinal Ganglion Cells Deep Learning Prognosis Female
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Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning.

Translational vision science & technology Oct 3, 2023
PURPOSE: To assess the performance of a perimetric strategy using structure-function predictions from a deep learning (DL) model.
Humans Glaucoma Algorithms Deep Learning Retinal Ganglion Cells Visual Fields Visual Field Tests
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Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.

JAMA ophthalmology Apr 1, 2022
IMPORTANCE: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of end points in clinical trials.
Ocular Hypertension Deep Learning Humans Visual Field Tests Optic Nerve Diseases Glaucoma Female Glaucoma, Open-Angle Intraocular Pressure Male Middle Aged
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Identifying the Retinal Layers Linked to Human Contrast Sensitivity Via Deep Learning.

Investigative ophthalmology & visual science Feb 1, 2022
PURPOSE: Luminance contrast is the fundamental building block of human spatial vision. Therefore contrast sensitivity, the reciprocal of contrast threshold required for target detection, has been a barometer of human visual function. Although retinal...
Middle Aged Deep Learning Visual Acuity Tomography, Optical Coherence Aged, 80 and over Young Adult Humans Adult Male Neural Networks, Computer Glaucoma, Open-Angle Female Retinal Neurons Macular Degeneration Aged Visual Fields Visual Field Tests Contrast Sensitivity
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Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest.

Translational vision science & technology Jul 1, 2021
PURPOSE: To compare change over time in eye-specific optical coherence tomography (OCT) retinal nerve fiber layer (RNFL)-based region-of-interest (ROI) maps developed using unsupervised deep-learning auto-encoders (DL-AE) to circumpapillary RNFL (cpR...
Visual Fields Visual Field Tests Disease Progression Optic Nerve Diseases Deep Learning Glaucoma, Open-Angle Nerve Fibers Humans Retinal Ganglion Cells Glaucoma Intraocular Pressure
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