AIMC Topic: Glaucoma, Open-Angle

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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...
Deep Learning Tomography, Optical Coherence Retina Visual Fields Glaucoma, Open-Angle Humans Glaucoma Cross-Sectional Studies Intraocular Pressure
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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...
Nerve Fibers Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases Humans Glaucoma Intraocular Pressure Glaucoma, Open-Angle Disease Progression Deep Learning
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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.
Deep Learning Visual Fields Humans Adult Visual Field Tests Algorithms ROC Curve Cross-Sectional Studies Glaucoma, Open-Angle Female Tomography, Optical Coherence Intraocular Pressure Gonioscopy Aged Nerve Fibers Male Slit Lamp Microscopy Retinal Ganglion Cells Aged, 80 and over Middle Aged
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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.
Visual Field Tests Glaucoma, Open-Angle Ocular Hypertension Tonometry, Ocular Forecasting Humans Male Machine Learning Female Middle Aged Algorithms Reproducibility of Results Diagnosis, Computer-Assisted Aged Cohort Studies Intraocular Pressure Visual Fields
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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.
Deep Learning ROC Curve Predictive Value of Tests Area Under Curve Fundus Oculi Optic Nerve Diseases False Positive Reactions Diagnostic Techniques, Ophthalmological Photography Glaucoma, Open-Angle Databases, Factual Female Sensitivity and Specificity Cross-Sectional Studies Male Humans
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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...
Sensitivity and Specificity Intraocular Pressure Male Middle Aged Diagnosis, Computer-Assisted Humans Retrospective Studies Female Aged Adult Optic Nerve Diseases Diagnostic Techniques, Ophthalmological Photography Ophthalmologists Glaucoma, Open-Angle Deep Learning ROC Curve Area Under Curve Observer Variation Optic Disk
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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.
Retrospective Studies Female Adult Intraocular Pressure Male Middle Aged Deep Learning ROC Curve Area Under Curve Tomography, Optical Coherence Humans Image Interpretation, Computer-Assisted Photography Nerve Fibers Glaucoma, Open-Angle Retinal Ganglion Cells Ophthalmologic Surgical Procedures Diagnostic Techniques, Ophthalmological
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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...
Nerve Fibers Retinal Ganglion Cells Retinal Vessels Glaucoma, Open-Angle Middle Aged Case-Control Studies ROC Curve Area Under Curve Tomography, Optical Coherence Aged Adult Cross-Sectional Studies Humans Intraocular Pressure Neural Networks, Computer Male Artificial Intelligence Female
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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...
Optic Disk Disease Progression Humans Aged Retinal Ganglion Cells Retrospective Studies Tonometry, Ocular Adult Unsupervised Machine Learning Visual Field Tests Female Intraocular Pressure Principal Component Analysis Optic Nerve Diseases Male Tomography, Optical Coherence Glaucoma, Open-Angle Middle Aged Nerve Fibers
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Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects.

Journal of glaucoma Dec 1, 2017
PURPOSE: Existing summary statistics based upon optical coherence tomographic (OCT) scans and/or visual fields (VFs) are suboptimal for distinguishing between healthy and glaucomatous eyes in the clinic. This study evaluates the extent to which a hyb...
Intraocular Pressure Glaucoma, Open-Angle Humans Tomography, Optical Coherence Ocular Hypertension Nerve Fibers Neural Networks, Computer Retinal Ganglion Cells Machine Learning Visual Fields Reproducibility of Results
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