AIMC Topic: Glaucoma, Open-Angle

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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...
Female Aged Aged, 80 and over Young Adult Adult Humans Neural Networks, Computer Macular Degeneration Visual Fields Visual Field Tests Contrast Sensitivity Glaucoma, Open-Angle Retinal Neurons Male Middle Aged Deep Learning Visual Acuity Tomography, Optical Coherence
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Predicting 10-2 Visual Field From Optical Coherence Tomography in Glaucoma Using Deep Learning Corrected With 24-2/30-2 Visual Field.

Translational vision science & technology Nov 1, 2021
PURPOSE: To investigate whether a correction based on a Humphrey field analyzer (HFA) 24-2/30-2 visual field (VF) can improve the prediction performance of a deep learning model to predict the HFA 10-2 VF test from macular optical coherence tomograph...
Retina Visual Fields Glaucoma, Open-Angle Intraocular Pressure Deep Learning Tomography, Optical Coherence Humans Glaucoma Cross-Sectional Studies
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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...
Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Glaucoma, Open-Angle Glaucoma Intraocular Pressure Disease Progression Deep Learning Nerve Fibers Humans
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Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

JAMA ophthalmology Apr 1, 2020
IMPORTANCE: Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.
Humans Algorithms Female Aged Aged, 80 and over Deep Learning ROC Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Adult Cross-Sectional Studies Intraocular Pressure Male Middle Aged Visual Field Tests Glaucoma, Open-Angle Gonioscopy Slit Lamp Microscopy
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Accuracy of Kalman Filtering in Forecasting Visual Field and Intraocular Pressure Trajectory in Patients With Ocular Hypertension.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely to progress to open-angle glaucoma can assist clinicians with deciding on the frequency of monitoring and the potential benefit of early treatment.
Humans Female Reproducibility of Results Aged Machine Learning Algorithms Forecasting Visual Fields Intraocular Pressure Visual Field Tests Male Glaucoma, Open-Angle Middle Aged Ocular Hypertension Diagnosis, Computer-Assisted Tonometry, Ocular Cohort Studies
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Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.
Optic Nerve Diseases False Positive Reactions Diagnostic Techniques, Ophthalmological Humans Photography Databases, Factual Predictive Value of Tests Male Glaucoma, Open-Angle Female Area Under Curve Sensitivity and Specificity Deep Learning Fundus Oculi Cross-Sectional Studies ROC Curve
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Evaluation of a Deep Learning System For Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Journal of glaucoma Dec 1, 2019
PRECIS: Pegasus outperformed 5 of the 6 ophthalmologists in terms of diagnostic performance, and there was no statistically significant difference between the deep learning system and the "best case" consensus between the ophthalmologists. The agreem...
Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Photography Ophthalmologists Glaucoma, Open-Angle Sensitivity and Specificity Intraocular Pressure Male Middle Aged Diagnosis, Computer-Assisted Deep Learning ROC Curve Area Under Curve Observer Variation Optic Disk Humans Retrospective Studies Female Aged Adult
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Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.

Journal of glaucoma Mar 1, 2019
UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transformation technique can be an economical as well as an effective tool for early detection of glaucomatous RNFL defect.
Ophthalmologic Surgical Procedures Diagnostic Techniques, Ophthalmological Photography Glaucoma, Open-Angle Area Under Curve Intraocular Pressure Tomography, Optical Coherence Humans Male Image Interpretation, Computer-Assisted Retrospective Studies Nerve Fibers Middle Aged Female Retinal Ganglion Cells Deep Learning Adult ROC Curve
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Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Journal of glaucoma Sep 1, 2018
PURPOSE: To evaluate the relationship between macular vessel density and ganglion cell to inner plexiform layer thickness (GCIPLT) and to compare their diagnostic performance. We attempted to develop a new combined parameter using an artificial neura...
Cross-Sectional Studies Intraocular Pressure Male Middle Aged Case-Control Studies Neural Networks, Computer Artificial Intelligence Female Aged Adult ROC Curve Retinal Vessels Humans Area Under Curve Glaucoma, Open-Angle Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells
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Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Investigative ophthalmology & visual science Jun 1, 2018
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progres...
Principal Component Analysis Tomography, Optical Coherence Nerve Fibers Optic Disk Retinal Ganglion Cells Visual Field Tests Optic Nerve Diseases Glaucoma, Open-Angle Tonometry, Ocular Humans Retrospective Studies Female Aged Adult Intraocular Pressure Male Middle Aged Disease Progression Unsupervised Machine Learning
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