AIMC Topic: Visual Field Tests

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Deep learning model to predict visual field in central 10° from optical coherence tomography measurement in glaucoma.

The British journal of ophthalmology Jun 27, 2020
BACKGROUND/AIM: To train and validate the prediction performance of the deep learning (DL) model to predict visual field (VF) in central 10° from spectral domain optical coherence tomography (SD-OCT).
Humans Glaucoma Female Aged Cross-Sectional Studies Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Gonioscopy Intraocular Pressure Male Middle Aged Deep Learning Predictive Value of Tests
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The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields.

Scientific reports May 12, 2020
The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consisted of 82,433 VFs from 16,836 eyes. Testing dataset 1 consisted of test-retest VFs from 104 eyes wit...
Adult Sensitivity and Specificity Intraocular Pressure Male Middle Aged Disease Progression Humans Female Reproducibility of Results Glaucoma, Open-Angle Deep Learning Visual Fields Linear Models Visual Field Tests Eye
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Predicting the Glaucomatous Central 10-Degree Visual Field From Optical Coherence Tomography Using Deep Learning and Tensor Regression.

American journal of ophthalmology May 6, 2020
PURPOSE: To predict the visual field (VF) of glaucoma patients within the central 10° from optical coherence tomography (OCT) measurements using deep learning and tensor regression.
Axial Length, Eye Visual Field Tests Optic Nerve Diseases Glaucoma, Open-Angle Gonioscopy Slit Lamp Microscopy Adult Sensitivity and Specificity Cross-Sectional Studies Humans Intraocular Pressure Retrospective Studies Male Female Middle Aged Aged Deep Learning Visual Acuity Vision Disorders Tomography, Optical Coherence Visual Fields
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Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

American journal of ophthalmology Apr 2, 2020
PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition.
Deep Learning ROC Curve Area Under Curve Optic Disk Visual Field Tests Female Reproducibility of Results Sensitivity and Specificity Intraocular Pressure Male Optic Nerve Diseases Photography Humans Neural Networks, Computer Glaucoma Algorithms
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Beyond Performance Metrics: Automatic Deep Learning Retinal OCT Analysis Reproduces Clinical Trial Outcome.

Ophthalmology Dec 23, 2019
PURPOSE: To validate the efficacy of a fully automatic, deep learning-based segmentation algorithm beyond conventional performance metrics by measuring the primary outcome of a clinical trial for macular telangiectasia type 2 (MacTel2).
Fluorescein Angiography Deep Learning Ciliary Neurotrophic Factor Retinal Photoreceptor Cell Inner Segment Retinal Vessels Humans Treatment Outcome Retinal Photoreceptor Cell Outer Segment Retinal Telangiectasis Female Visual Acuity Drug Implants Reproducibility of Results Tomography, Optical Coherence Male Visual Fields Visual Field Tests
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Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients.

Japanese journal of ophthalmology Dec 17, 2019
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Gonioscopy Myopia Slit Lamp Microscopy Diagnosis, Computer-Assisted Low Tension Glaucoma Humans ROC Curve Machine Learning Area Under Curve Adult Female Tomography, Optical Coherence Cross-Sectional Studies Young Adult Intraocular Pressure Male Disease Progression
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Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma.

Ophthalmology Dec 12, 2019
PURPOSE: To quantify the central visual field (VF) loss patterns in glaucoma using artificial intelligence.
Aged Vision Disorders Bayes Theorem Humans Cross-Sectional Studies Visual Fields Glaucoma Intraocular Pressure Visual Field Tests Artificial Intelligence Male Retrospective Studies Middle Aged Female
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Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.

American journal of ophthalmology Nov 12, 2019
PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs.
Area Under Curve Tomography, Optical Coherence Fundus Oculi Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Photography Physical Examination Glaucoma, Open-Angle Male Middle Aged Deep Learning Humans ROC Curve Algorithms Vision Disorders Retrospective Studies Female Aged Cross-Sectional Studies Intraocular Pressure Gonioscopy
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Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology Sep 30, 2019
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.
Aged Adult Male Middle Aged Deep Learning Humans Glaucoma Female Visual Fields Visual Field Tests Vision Disorders Optic Nerve Diseases Predictive Value of Tests Diagnostic Techniques, Ophthalmological Nerve Fibers Optic Disk Retinal Ganglion Cells
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Machine Learning in the Detection of the Glaucomatous Disc and Visual Field.

Seminars in ophthalmology May 27, 2019
Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of ...
Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Humans Glaucoma Machine Learning Diagnosis, Computer-Assisted Vision Disorders Visual Fields Visual Field Tests
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