AIMC Topic: Intraocular Pressure
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Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.
Ophthalmology
Dec 25, 2020
PURPOSE: Rule-based approaches to determining glaucoma progression from visual fields (VFs) alone are discordant and have tradeoffs. To detect better when glaucoma progression is occurring, we used a longitudinal data set of merged VF and clinical da...
Deep learning classification of early normal-tension glaucoma and glaucoma suspects using Bruch's membrane opening-minimum rim width and RNFL.
Scientific reports
Nov 4, 2020
We aimed to classify early normal-tension glaucoma (NTG) and glaucoma suspect (GS) using Bruch's membrane opening-minimum rim width (BMO-MRW), peripapillary retinal nerve fiber layer (RNFL), and the color classification of RNFL based on a deep-learni...
Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images.
The British journal of ophthalmology
Sep 26, 2020
BACKGROUND/AIMS: Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angl...
Detection of Glaucoma Deterioration in the Macular Region with Optical Coherence Tomography: Challenges and Solutions.
American journal of ophthalmology
Sep 18, 2020
PURPOSE: Macular imaging with optical coherence tomography (OCT) measures the most critical retinal ganglion cells (RGCs) in the human eye. The goal of this perspective is to review the challenges to detection of glaucoma progression with macular OCT...
Prediction of visual field from swept-source optical coherence tomography using deep learning algorithms.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Aug 26, 2020
PURPOSE: To develop a deep learning method to predict visual field (VF) from wide-angle swept-source optical coherence tomography (SS-OCT) and compare the performance of three Google Inception architectures.
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).
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...
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.
Aged
Adult
Sensitivity and Specificity
Cross-Sectional Studies
Intraocular Pressure
Male
Middle Aged
Deep Learning
Visual Acuity
Humans
Retrospective Studies
Female
Optic Nerve Diseases
Glaucoma, Open-Angle
Vision Disorders
Gonioscopy
Tomography, Optical Coherence
Slit Lamp Microscopy
Visual Fields
Axial Length, Eye
Visual Field Tests
Predicting Glaucoma before Onset Using Deep Learning.
Ophthalmology. Glaucoma
Apr 29, 2020
PURPOSE: To assess the accuracy of deep learning models to predict glaucoma development from fundus photographs several years before disease onset.
Using Deep Learning to Automate Goldmann Applanation Tonometry Readings.
Ophthalmology
Apr 25, 2020
PURPOSE: To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.
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