Glaucoma

ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.

Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases are fundus photography, scanning laser ophthalmoscope (SLO) and fluorescein angiography (FA). Typically, retinal vessel segmentation is carried out ei...

Visual Field Estimation by Probabilistic Classification.

The gold standard clinical tool for evaluating visual dysfunction in cases of glaucoma and other disorders of vision remains the visual field or threshold perimetry exam. Administration of this exam has evolved over the years into a sophisticated, standardized, automated algorithm that relies heavily on specifics of disease processes particular to common retinal disorders. The purpose of this stud...

Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and dis...

Machine Learning Techniques for Ophthalmic Data Processing: A Review.

Machine learning and especially deep learning techniques are dominating medical image and data analysis. This article reviews machine learning approac...

Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning.

The choroid provides oxygen and nourishment to the outer retina thus is related to the pathology of various ocular diseases. Optical coherence tomogra...

Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device.

Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and c...

Deep learning classification of early normal-tension glaucoma and glaucoma suspects using Bruch's membrane opening-minimum rim width and RNFL.

We aimed to classify early normal-tension glaucoma (NTG) and glaucoma suspect (GS) using Bruch's membrane opening-minimum rim width (BMO-MRW), peripap...

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

PURPOSE: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting gl...

Deep learning in glaucoma with optical coherence tomography: a review.

Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has made significant breakthroughs in medical imaging, par...

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.

Health data that are publicly available are valuable resources for digital health research. Several public datasets containing ophthalmological imagin...

Deep-learning-based enhanced optic-disc photography.

Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient ...

Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images.

BACKGROUND/AIMS: Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomog...

Detection of Glaucoma Deterioration in the Macular Region with Optical Coherence Tomography: Challenges and Solutions.

PURPOSE: Macular imaging with optical coherence tomography (OCT) measures the most critical retinal ganglion cells (RGCs) in the human eye. The goal o...

An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.

Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes ...

[Artificial intelligence for eye care].

Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already...

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective.

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology...

An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma.

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 role of neuroinflammation in the pathogenesis of glaucoma neurodegeneration.

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...

Artificial intelligence and deep learning in glaucoma: Current state and future prospects.

Over the past few years, there has been an unprecedented and tremendous excitement for artificial intelligence (AI) research in the field of Ophthalmo...

Artificial Intelligence and Glaucoma: Illuminating the Black Box.