AIMC Topic: Optic Nerve Diseases

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Differentiating Glaucomatous Optic Neuropathy From Non-glaucomatous Optic Neuropathies Using Deep Learning Algorithms.

American journal of ophthalmology
PURPOSE: A deep learning framework to differentiate glaucomatous optic disc changes due to glaucomatous optic neuropathy (GON) from non-glaucomatous optic disc changes due to non-glaucomatous optic neuropathies (NGONs).

Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements.

American journal of ophthalmology
PURPOSE: To estimate central 10-degree visual field (VF) map from spectral-domain optical coherence tomography (SD-OCT) retinal nerve fiber layer thickness (RNFL) measurements in glaucoma with artificial intelligence.

Research on Assistant Diagnosis of Fundus Optic Neuropathy Based on Deep Learning.

Current eye research
PURPOSE: The purpose of this study was to use the neural network to distinguish optic edema (ODE), and optic atrophy from normal fundus images and try to use visualization to explain the artificial intelligence methods.

Imaging of the optic nerve: technological advances and future prospects.

The Lancet. Neurology
Over the past decade, ocular imaging strategies have greatly advanced the diagnosis and follow-up of patients with optic neuropathies. Developments in optic nerve imaging have specifically improved the care of patients with papilloedema and idiopathi...

Deep learning: applications in retinal and optic nerve diseases.

Clinical & experimental optometry
Deep learning (DL) represents a paradigm-shifting, burgeoning field of research with emerging clinical applications in optometry. Unlike traditional programming, which relies on human-set specific rules, DL works by exposing the algorithm to a large ...

Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging.

Ophthalmology
PURPOSE: To develop and validate a deep learning (DL) system for predicting each point on visual fields (VFs) from disc and OCT imaging and derive a structure-function mapping.

Deep learning on fundus images detects glaucoma beyond the optic disc.

Scientific reports
Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. Here, we propose a methodology that advances explainable deep learning in the field of glaucoma dete...

Development and evaluation of a deep learning model for the detection of multiple fundus diseases based on colour fundus photography.

The British journal of ophthalmology
AIM: To explore and evaluate an appropriate deep learning system (DLS) for the detection of 12 major fundus diseases using colour fundus photography.

An objective structural and functional reference standard in glaucoma.

Scientific reports
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using cle...