Latest AI and machine learning research in glaucoma for healthcare professionals.
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 angle-closure glaucoma.
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 imaging and propose ways to enhance its performance.
Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes ...
Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already...
The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology...
PURPOSE: The purpose of this study was to classify the spatial patterns of retinal nerve fiber layer thickness (RNFLT) and assess their associations w...
The chapter is a review enclosed in the volume "Glaucoma: A pancitopatia of the retina and beyond." No cure exists for glaucoma. Knowledge on the mole...
Over the past few years, there has been an unprecedented and tremendous excitement for artificial intelligence (AI) research in the field of Ophthalmo...
UNLABELLED: Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of art...
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is ...
BACKGROUND/AIM: To train and validate the prediction performance of the deep learning (DL) model to predict visual field (VF) in central 10° from spec...
PURPOSE: The purpose of this study was to evaluate the accuracy of the convolutional neural network (CNN) model in glaucoma identification with three ...
PURPOSE: To illustrate what is inside the so-called black box of deep learning models (DLMs) so that clinicians can have greater confidence in the con...
Ophthalmological analysis plays a vital role in the diagnosis of various eye diseases, such as glaucoma, retinitis pigmentosa (RP), and diabetic and h...
With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligenc...
PURPOSE: The cup-to-disc ratio (CDR), a clinical metric of the relative size of the optic cup to the optic disc, is a key indicator of glaucoma, a chr...
In this work, we develop a robust, extensible tool to automatically and accurately count retinal ganglion cell axons in optic nerve (ON) tissue images...
The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consis...