AIMC Topic: Optic Disk
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Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects.
The British journal of ophthalmology
Jun 20, 2024
BACKGROUND/AIMS: To assess the performance of deep-learning (DL) models for prediction of conversion to normal-tension glaucoma (NTG) in normotensive glaucoma suspect (GS) patients.
Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.
Scientific reports
May 23, 2024
Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of retinal ganglion cells, leading to irreversible blindness worldwide. Therefore, timely and accurate diagnosis of glaucoma is crucial, enabling early inte...
SAMCF: Adaptive global style alignment and multi-color spaces fusion for joint optic cup and disc segmentation.
Computers in biology and medicine
May 21, 2024
The optic cup (OC) and optic disc (OD) are two critical structures in retinal fundus images, and their relative positions and sizes are essential for effectively diagnosing eye diseases. With the success of deep learning in computer vision, deep lear...
JOINEDTrans: Prior guided multi-task transformer for joint optic disc/cup segmentation and fovea detection.
Computers in biology and medicine
May 17, 2024
Deep learning-based image segmentation and detection models have largely improved the efficiency of analyzing retinal landmarks such as optic disc (OD), optic cup (OC), and fovea. However, factors including ophthalmic disease-related lesions and low ...
Progression or Aging? A Deep Learning Approach for Distinguishing Glaucoma Progression From Age-Related Changes in OCT Scans.
American journal of ophthalmology
May 3, 2024
PURPOSE: To develop deep learning (DL) algorithm to detect glaucoma progression using optical coherence tomography (OCT) images, in the absence of a reference standard.
Glaucoma
Algorithms
Retrospective Studies
Female
Aged
Humans
Neural Networks, Computer
Nerve Fibers
Optic Disk
Retinal Ganglion Cells
Visual Fields
Disease Progression
Optic Nerve Diseases
Glaucoma, Open-Angle
Intraocular Pressure
Deep Learning
Male
Follow-Up Studies
Aging
Tomography, Optical Coherence
Middle Aged
Recognition of Glaucomatous Fundus Images Using Machine Learning Methods Based on Optic Nerve Head Topographic Features.
Journal of glaucoma
Mar 29, 2024
PRCIS: Machine learning classifiers are an effective approach to detecting glaucomatous fundus images based on optic disc topographic features making it a straightforward and effective approach.
Development of a deep learning model to distinguish the cause of optic disc atrophy using retinal fundus photography.
Scientific reports
Mar 1, 2024
The differential diagnosis for optic atrophy can be challenging and requires expensive, time-consuming ancillary testing to determine the cause. While Leber's hereditary optic neuropathy (LHON) and optic neuritis (ON) are both clinically significant ...
Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.
American journal of ophthalmology
Feb 12, 2024
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...
Intraocular Pressure
Male
Middle Aged
Disease Progression
Humans
Algorithms
Visual Fields
Glaucoma
Retrospective Studies
Area Under Curve
Deep Learning
Visual Field Tests
Female
ROC Curve
Tomography, Optical Coherence
Nerve Fibers
Optic Nerve Diseases
Aged
Follow-Up Studies
Optic Disk
Glaucoma, Open-Angle
Vision Disorders
Retinal Ganglion Cells
A multi-label transformer-based deep learning approach to predict focal visual field progression.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Feb 9, 2024
PURPOSE: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression...
Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images.
Ophthalmology. Retina
Jan 26, 2024
OBJECTIVE: We aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images.
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