Glaucoma

Telemonitoring Tools for Glaucoma Patients: A Systematic Review of Current Trends and Applications.

: In 2010, approximately 60.5 million people were affected by glaucoma, making it the leading cause of permanent vision impairment globally. With the rise of telehealth tools and technological advancements in glaucoma care, this review aims to provide an up-to-date analysis regarding remote monitoring systems in glaucoma management. : A systematic literature search (in compliance with PRISMA guide...

Artificial Intelligence in Glaucoma: Advances in Diagnosis, Progression Forecasting, and Surgical Outcome Prediction.

Glaucoma is a leading cause of irreversible blindness, with challenges persisting in early diagnosis, disease progression, and surgical outcome prediction. Recent advances in artificial intelligence have enabled significant progress by extracting clinically relevant patterns from structural, functional, and molecular data. This review outlines the current applications of artificial intelligence in...

High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis ...

Opening the black box of deep learning: Validating the statistical association between explainable artificial intelligence (XAI) and clinical domain knowledge in fundus image-based glaucoma diagnosis

While deep learning has exhibited remarkable predictive capabilities in various medical image tasks, its inherent black-box nature has hindered its ...

Enhancing Fundus Image-based Glaucoma Screening via Dynamic Global-Local Feature Integration

With the advancements in medical artificial intelligence (AI), fundus image classifiers are increasingly being applied to assist in ophthalmic diagn...

3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia -- A Key to Improving Glaucoma Diagnosis in Myopic Populations

Purpose: To characterize the 3D structural phenotypes of the optic nerve head (ONH) in patients with glaucoma, high myopia, and concurrent high myop...

Rethinking Glaucoma Calibration: Voting-Based Binocular and Metadata Integration

Glaucoma is an incurable ophthalmic disease that damages the optic nerve, leads to vision loss, and ranks among the leading causes of blindness worl...

Analysis of human visual field information using machine learning methods and assessment of their accuracy

Subject of research: is the study of methods for analyzing perimetric images for the diagnosis and control of glaucoma diseases. Objects of research...

X-GAN: A Generative AI-Powered Unsupervised Model for High-Precision Segmentation of Retinal Main Vessels toward Early Detection of Glaucoma

Structural changes in main retinal blood vessels serve as critical biomarkers for the onset and progression of glaucoma. Identifying these vessels i...

Multimodal Artificial Intelligence Models Predicting Glaucoma Progression Using Electronic Health Records and Retinal Nerve Fiber Layer Scans.

PURPOSE: The purpose of this study was to develop models that predict which patients with glaucoma will progress to require surgery, combining structu...

GONet: A Generalizable Deep Learning Model for Glaucoma Detection

Glaucomatous optic neuropathy (GON) is a prevalent ocular disease that can lead to irreversible vision loss if not detected early and treated. The t...

MaxGlaViT: A novel lightweight vision transformer-based approach for early diagnosis of glaucoma stages from fundus images

Glaucoma is a prevalent eye disease that progresses silently without symptoms. If not detected and treated early, it can cause permanent vision loss...

Ocular Disease Classification Using CNN with Deep Convolutional Generative Adversarial Network

The Convolutional Neural Network (CNN) has shown impressive performance in image classification because of its strong learning capabilities. However...

Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?

The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1...

Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye

The prevalence of ocular illnesses is growing globally, presenting a substantial public health challenge. Early detection and timely intervention ar...

DeepEyeNet: Adaptive Genetic Bayesian Algorithm Based Hybrid ConvNeXtTiny Framework For Multi-Feature Glaucoma Eye Diagnosis

Glaucoma is a leading cause of irreversible blindness worldwide, emphasizing the critical need for early detection and intervention. In this paper, ...

Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends

The emergence of artificial intelligence (AI), particularly deep learning (DL), has marked a new era in the realm of ophthalmology, offering transfo...

DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation

Retinal vascular morphology is crucial for diagnosing diseases such as diabetes, glaucoma, and hypertension, making accurate segmentation of retinal...

Artificial Intelligence for Optical Coherence Tomography in Glaucoma.

PURPOSE: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant ...

End-to-end evaluation of white matter microstructure of the visual pathway in asymmetric glaucoma

Diffusion magnetic resonance imaging is a non-invasive neuroimaging technique that enables in vivo evaluation of white matter microstructure, providin...