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Optic Nerve Diseases

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Ethambutol-induced optic neuropathy in renal disorder: a clinico-electrophysiological study.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To report the spectrum of ethambutol induced optic neuropathy in a group of renal patients with tuberculosis and the role of visual evoked response (VER) in evaluating this disorder.

Deep Learning for Retinal Image Quality Assessment of Optic Nerve Head Disorders.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Deep learning (DL)-based retinal image quality assessment (RIQA) algorithms have been gaining popularity, as a solution to reduce the frequency of diagnostically unusable images. Most existing RIQA tools target retinal conditions, with a dearth of st...

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
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.

Assessing the Efficacy of Synthetic Optic Disc Images for Detecting Glaucomatous Optic Neuropathy Using Deep Learning.

Translational vision science & technology
PURPOSE: Deep learning architectures can automatically learn complex features and patterns associated with glaucomatous optic neuropathy (GON). However, developing robust algorithms requires a large number of data sets. We sought to train an adversar...

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

Translational vision science & technology
PURPOSE: We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness.

Trends in the Prevalence of Common Retinal and Optic Nerve Diseases in China: An Artificial Intelligence Based National Screening.

Translational vision science & technology
PURPOSE: Retinal and optic nerve diseases have become the primary cause of irreversible vision loss and blindness. However, there is still a lack of thorough evaluation regarding their prevalence in China.

Deep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets.

Translational vision science & technology
PURPOSE: To develop a three-dimensional (3D) deep learning algorithm to detect glaucoma using spectral-domain optical coherence tomography (SD-OCT) optic nerve head (ONH) cube scans and validate its performance on ethnically diverse real-world datase...

Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.

JAMA ophthalmology
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.

Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop a deep learning system for automated glaucomatous optic neuropathy (GON) detection using ultra-widefield fundus (UWF) images.

Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: To date, deep learning-based detection of optic disc abnormalities in color fundus photographs has mostly been limited to the field of glaucoma. However, many life-threatening systemic and neurological conditions can manifest as optic dis...