AI Medical Compendium Topic

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Retinal Vessels

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3DVascNet: An Automated Software for Segmentation and Quantification of Mouse Vascular Networks in 3D.

Arteriosclerosis, thrombosis, and vascular biology
BACKGROUND: Analysis of vascular networks is an essential step to unravel the mechanisms regulating the physiological and pathological organization of blood vessels. So far, most of the analyses are performed using 2-dimensional projections of 3-dime...

A Microvascular Segmentation Network Based on Pyramidal Attention Mechanism.

Sensors (Basel, Switzerland)
The precise segmentation of retinal vasculature is crucial for the early screening of various eye diseases, such as diabetic retinopathy and hypertensive retinopathy. Given the complex and variable overall structure of retinal vessels and their delic...

VascuConNet: an enhanced connectivity network for vascular segmentation.

Medical & biological engineering & computing
Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber bundle segmentation. Enhancing the continuity of segmentation outcomes represents a pivotal challenge ...

Partial class activation mapping guided graph convolution cascaded U-Net for retinal vessel segmentation.

Computers in biology and medicine
Accurate segmentation of retinal vessels in fundus images is of great importance for the diagnosis of numerous ocular diseases. However, due to the complex characteristics of fundus images, such as various lesions, image noise and complex background,...

Identification of diabetic retinopathy classification using machine learning algorithms on clinical data and optical coherence tomography angiography.

Eye (London, England)
BACKGROUND: To apply machine learning (ML) algorithms to perform multiclass diabetic retinopathy (DR) classification using both clinical data and optical coherence tomography angiography (OCTA).

Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity.

Ophthalmology
PURPOSE: To evaluate whether providing clinicians with an artificial intelligence (AI)-based vascular severity score (VSS) improves consistency in the diagnosis of plus disease in retinopathy of prematurity (ROP).

Artificial intelligence in therapeutic management of hyperlipidemic ocular pathology.

Experimental eye research
Hyperlipidemia has many ocular manifestations, the most prevalent being retinal vascular occlusion. Hyperlipidemic lesions and occlusions to the vessels supplying the retina result in permanent blindness, necessitating prompt detection and treatment....

ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration.

Medical & biological engineering & computing
Retinal image registration is of utmost importance due to its wide applications in medical practice. In this context, we propose ConKeD, a novel deep learning approach to learn descriptors for retinal image registration. In contrast to current regist...

Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence.

BMJ open ophthalmology
OBJECTIVES: This study aimed to quantitatively evaluate optic nerve head and retinal vascular parameters in children with hyperopia in relation to age and spherical equivalent refraction (SER) using artificial intelligence (AI)-based analysis of colo...

LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation.

Scientific reports
Blinding eye diseases are often related to changes in retinal structure, which can be detected by analysing retinal blood vessels in fundus images. However, existing techniques struggle to accurately segment these delicate vessels. Although deep lear...