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Retinal Vessels

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Retinal imaging and Alzheimer's disease: a future powered by Artificial Intelligence.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Alzheimer's disease (AD) is a neurodegenerative condition that primarily affects brain tissue. Because the retina and brain share the same embryonic origin, visual deficits have been reported in AD patients. Artificial Intelligence (AI) has recently ...

High-precision retinal blood vessel segmentation based on a multi-stage and dual-channel deep learning network.

Physics in medicine and biology
The high-precision segmentation of retinal vessels in fundus images is important for the early diagnosis of ophthalmic diseases. However, the extraction for microvessels is challenging due to their characteristics of low contrast and high structural ...

Artificial Intelligence-based quantitative evaluation of retinal vascular parameters in thyroid-associated ophthalmopathy.

Endocrine
PURPOSE: Thyroid-associated ophthalmopathy (TAO) may result in increased metabolism and abnormalities in microcirculation. The fractal dimension (Df) of retinal vessels has been shown to be related to the pathology of a number of ophthalmic disorders...

CoVi-Net: A hybrid convolutional and vision transformer neural network for retinal vessel segmentation.

Computers in biology and medicine
Retinal vessel segmentation plays a crucial role in the diagnosis and treatment of ocular pathologies. Current methods have limitations in feature fusion and face challenges in simultaneously capturing global and local features from fundus images. To...

Using Deep Learning to Segment Retinal Vascular Leakage and Occlusion in Retinal Vasculitis.

Ocular immunology and inflammation
PURPOSE: Retinal vasculitis (RV) is characterised by retinal vascular leakage, occlusion or both on fluorescein angiography (FA). There is no standard scheme available to segment RV features. We aimed to develop a deep learning model to segment both ...

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BMC geriatrics
BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impair...

Ultra-wide field and new wide field composite retinal image registration with AI-enabled pipeline and 3D distortion correction algorithm.

Eye (London, England)
PURPOSE: This study aimed to compare a new Artificial Intelligence (AI) method to conventional mathematical warping in accurately overlaying peripheral retinal vessels from two different imaging devices: confocal scanning laser ophthalmoscope (cSLO) ...

Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity.

Medical & biological engineering & computing
Retinal vascular tortuosity is an excessive bending and twisting of the blood vessels in the retina that is associated with numerous health conditions. We propose a novel methodology for the automated assessment of the retinal vascular tortuosity fro...

Automated segmentation of ultra-widefield fluorescein angiography of diabetic retinopathy using deep learning.

The British journal of ophthalmology
BACKGROUND/AIMS: Retinal capillary non-perfusion (NP) and neovascularisation (NV) are two of the most important angiographic changes in diabetic retinopathy (DR). This study investigated the feasibility of using deep learning (DL) models to automatic...

Deep-learning segmentation method for optical coherence tomography angiography in ophthalmology.

Journal of biophotonics
PURPOSE: The optic disc and the macular are two major anatomical structures in the human eye. Optic discs are associated with the optic nerve. Macular mainly involves degeneration and impaired function of the macular region. Reliable optic disc and m...