AIMC Topic: Plaque, Atherosclerotic

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Automatic generation and risk stratification of carotid plaque in virtual shear wave elastography using a generative adversarial network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Shear wave elastography (SWE) is an effective ultrasound imaging technique for assessing carotid plaque vulnerability. However, acquiring SWE images typically requires costly specialized equipment and must be performed by experienced radiologists, wh...

SML-Net: Semi-supervised multi-task learning network for carotid plaque segmentation and classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Carotid ultrasound image segmentation and classification are crucial in assessing the severity of carotid plaques which serve as a major cause of ischemic stroke. Although many methods are employed for carotid plaque segmentation and classification, ...

FeaCL: Carotid plaque classification from ultrasound images using feature-level and instance-level contrast learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The classification of carotid plaques from ultrasound images in clinical application is crucial for predicting patient risks of cardiovascular and cerebrovascular diseases, as well as for developing appropriate treatment strategies. Although the effe...

A plaque recognition algorithm for coronary OCT images by Dense Atrous Convolution and attention mechanism.

PloS one
Currently, plaque segmentation in Optical Coherence Tomography (OCT) images of coronary arteries is primarily carried out manually by physicians, and the accuracy of existing automatic segmentation techniques needs further improvement. To furnish eff...

Research on ischemic stroke risk assessment based on CTA radiomics and machine learning.

BMC medical imaging
BACKGROUND: The study explores the value of a model constructed by integrating CTA-based carotid plaque radiomic features, clinical risk factors, and plaque imaging characteristics for prognosticating the risk of ischemic stroke.

Artificial Intelligence in CT Angiography for the Detection of Coronary Artery Stenosis and Calcified Plaque: A Systematic Review and Meta-analysis.

Academic radiology
PURPOSE: We aimed to evaluate the diagnostic performance of artificial intelligence (AI) in detecting coronary artery stenosis and calcified plaque on CT angiography (CTA), comparing its diagnostic performance with that of radiologists.

AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.

Circulation. Cardiovascular imaging
BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is known about sex-specific patterns in their prognostic value. This study aimed to define sex differences in the coronary atherosclerotic phenotypes assesse...

High-Resolution Magnetic Resonance Imaging Radiomics for Identifying High-Risk Intracranial Plaques.

Translational stroke research
The rupture of vulnerable plaques is the principal cause of luminal thrombosis in acute ischemic stroke. The identification of plaque features that indicate risk for disruption may predict cerebrovascular events. Here, we aimed to build a high-risk i...