AIMC Topic: Plaque, Atherosclerotic

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Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks.

IEEE transactions on medical imaging
Coronary heart disease is a common cause of death despite being preventable. To treat the underlying plaque deposits in the arterial walls, intravascular optical coherence tomography can be used by experts to detect and characterize the lesions. In c...

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide compl...

Relationship of femoral artery ultrasound measures of atherosclerosis with chronic kidney disease.

Journal of vascular surgery
BACKGROUND: Chronic kidney disease (CKD) is strongly associated with peripheral artery disease (PAD). Detection of subclinical PAD may allow early interventions for or prevention of PAD in persons with CKD. Whether the presence of atherosclerotic pla...

Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis ...

A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound.

IEEE journal of biomedical and health informatics
Characterization of carotid plaque composition, more specifically the amount of lipid core, fibrous tissue, and calcified tissue, is an important task for the identification of plaques that are prone to rupture, and thus for early risk estimation of ...

An artificial neural network method for lumen and media-adventitia border detection in IVUS.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to de...