AI Medical Compendium Topic

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Retinal Vessels

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ReIU: an efficient preliminary framework for Alzheimer patients based on multi-model data.

Frontiers in public health
The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibi...

Multi scale multi attention network for blood vessel segmentation in fundus images.

Scientific reports
Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the co...

DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.

Biomedical physics & engineering express
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped n...

Predicting branch retinal vein occlusion development using multimodal deep learning and pre-onset fundus hemisection images.

Scientific reports
Branch retinal vein occlusion (BRVO) is a leading cause of visual impairment in working-age individuals, though predicting its occurrence from retinal vascular features alone remains challenging. We developed a deep learning model to predict BRVO bas...

Deep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.

Eye (London, England)
PURPOSE: This study aims to develop a deep-learning-based software capable of detecting and differentiating microaneurysms (MAs) as hyporeflective or hyperreflective on structural optical coherence tomography (OCT) images in patients with non-prolife...

An effective vessel segmentation method using SLOA-HGC.

Scientific reports
Accurate segmentation of retinal blood vessels from retinal images is crucial for detecting and diagnosing a wide range of ophthalmic diseases. Our retinal blood vessel segmentation algorithm enhances microfine vessel extraction, improves edge textur...

(DA-U)Net: double attention UNet for retinal vessel segmentation.

BMC ophthalmology
BACKGROUND: Morphological changes in the retina are crucial and serve as valuable references in the clinical diagnosis of ophthalmic and cardiovascular diseases. However, the retinal vascular structure is complex, making manual segmentation time-cons...

Gabor-modulated depth separable convolution for retinal vessel segmentation in fundus images.

Computers in biology and medicine
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...