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Carotid Stenosis

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Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture.

Ultrasonic imaging
Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presented in this work. We report on 101 severely stenotic carotid plaque patients. A standard U-Net is compared with a dilated U-Net architecture in which th...

Detection of Asymptomatic Carotid Artery Stenosis in High-Risk Individuals of Stroke Using a Machine-Learning Algorithm.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Objective Asymptomatic carotid stenosis (ACS) is closely associated to the incidence of severe cerebrovascular diseases. Early identifying the individuals with ACS and its associated risk factors could be beneficial for primary prevention of stroke. ...

Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity.

Computational and mathematical methods in medicine
Carotid plaque echogenicity in ultrasound images has been found to be closely correlated with the risk of stroke in atherosclerotic patients. The automatic and accurate classification of carotid plaque echogenicity is of great significance for clinic...

Robot-Assisted Carotid Artery Stenting: A Safety and Feasibility Study.

Cardiovascular and interventional radiology
PURPOSE: Endovascular robotics is an emerging technology within the developing field of medical robotics. This was a prospective evaluation to assess safety and feasibility of robotic-assisted carotid artery stenting.

Ultrasound-based internal carotid artery plaque characterization using deep learning paradigm on a supercomputer: a cardiovascular disease/stroke risk assessment system.

The international journal of cardiovascular imaging
Visual or manual characterization and classification of atherosclerotic plaque lesions are tedious, error-prone, and time-consuming. The purpose of this study is to develop and design an automated carotid plaque characterization and classification sy...

Computational methods to automate the initial interpretation of lower extremity arterial Doppler and duplex carotid ultrasound studies.

Journal of vascular surgery
BACKGROUND: Lower extremity arterial Doppler (LEAD) and duplex carotid ultrasound studies are used for the initial evaluation of peripheral arterial disease and carotid stenosis. However, intra- and inter-laboratory variability exists between interpr...

Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database.

Biomechanics and modeling in mechanobiology
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...

Robot-assisted carotid artery stenting: outcomes, safety, and operational learning curve.

Neurosurgical focus
OBJECTIVE: Over the past 2 decades, robots have been increasingly used in surgeries to help overcome human limitations and perform precise and accurate tasks. Endovascular robots were pioneered in interventional cardiology, however, the CorPath GRX w...