AIMC Topic: Glaucoma

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Deep Learning Application to Detect Glaucoma with a Mixed Training Approach: Public Database and Expert-Labeled Glaucoma Population.

Ophthalmic research
INTRODUCTION: Artificial intelligence has real potential for early identification of ocular diseases such as glaucoma. An important challenge is the requirement for large databases properly selected, which are not easily obtained. We used a relativel...

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements.

American journal of ophthalmology
PURPOSE: To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements.

Autonomous assessment of spontaneous retinal venous pulsations in fundus videos using a deep learning framework.

Scientific reports
The presence or absence of spontaneous retinal venous pulsations (SVP) provides clinically significant insight into the hemodynamic status of the optic nerve head. Reduced SVP amplitudes have been linked to increased intracranial pressure and glaucom...

A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To distinguish functioning from failed filtration blebs (FBs) implementing a deep learning (DL) model on slit-lamp images.

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous successful examples in ophthalmology. However, much of the work has been focused on replicating the works of ophthalmologists. Given the analytical p...

Deep Learning for Localized Detection of Optic Disc Hemorrhages.

American journal of ophthalmology
PURPOSE: To develop an automated deep learning system for detecting the presence and location of disc hemorrhages in optic disc photographs.

Unraveling the complexity of Optical Coherence Tomography image segmentation using machine and deep learning techniques: A review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Optical Coherence Tomography (OCT) is an emerging technology that provides three-dimensional images of the microanatomy of biological tissue in-vivo and at micrometer-scale resolution. OCT imaging has been widely used to diagnose and manage various m...

Review of Visualization Approaches in Deep Learning Models of Glaucoma.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Glaucoma is a major cause of irreversible blindness worldwide. As glaucoma often presents without symptoms, early detection and intervention are important in delaying progression. Deep learning (DL) has emerged as a rapidly advancing tool to help ach...

Deep-learning approach to detect childhood glaucoma based on periocular photograph.

Scientific reports
Childhood glaucoma is one of the major causes of blindness in children, however, its diagnosis is of great challenge. The study aimed to demonstrate and evaluate the performance of a deep-learning (DL) model for detecting childhood glaucoma based on ...