AIMC Topic: Carotid Stenosis
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Recognition of early stage thigmotaxis in Morris water maze test with convolutional neural network.
PloS one
May 3, 2018
The Morris water maze test (MWM) is a useful tool to evaluate rodents' spatial learning and memory, but the outcome is susceptible to various experimental conditions. Thigmotaxis is a commonly observed behavioral pattern which is thought to be relate...
Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis.
Journal of biomedical semantics
May 10, 2016
BACKGROUND: In the United States, 795,000 people suffer strokes each year; 10-15 % of these strokes can be attributed to stenosis caused by plaque in the carotid artery, a major stroke phenotype risk factor. Studies comparing treatments for the manag...
Novel artificial intelligence approach in neurointerventional practice: Preliminary findings on filter movement and ischemic lesions in carotid artery stenting.
Clinical neurology and neurosurgery
Jul 1, 2025
BACKGROUND AND OBJECTIVES: Embolic protection devices (EPDs) used during carotid artery stenting (CAS) are crucial in reducing ischemic complications. Although minimizing the filter-type EPD movement is considered important, limited research has demo...
[Deep Learning-Based Artificial Intelligence Model for Automatic Carotid Plaque Identification].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Jul 30, 2024
This study aims at developing a dataset for determining the presence of carotid artery plaques in ultrasound images, composed of 1761 ultrasound images from 1165 participants. A deep learning architecture that combines bilinear convolutional neural n...
Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by fluctuating plaque surfaces with blood flow pulsation, is a dynamic characteristic of these plaques that has recently attracted attention. Detecting ...
PSAA-nnUNet: An Efficient Method for CT Carotid Artery Image Segmentation.
Advances in experimental medicine and biology
Jan 1, 2024
Carotid artery (CA) stenosis (CAS) constitutes a significant factor to ischaemic cerebrovascular events which exhibiting no overt symptoms in the early stages. Early detection of CAS can prevent ischaemic stroke and improve patient prognosis. In this...
Automated Deep Learning-based Single-Step Diameter Estimation of Carotid Arteries in B-mode Ultrasound.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Accurate measurement of blood vessel diameter on ultrasonic images is important in many vascular exams. In one of them, volumetric blood flow measurements, the volume flow rate is calculated by multiplying the time-averaged velocity with the cross-se...
Robot-assisted carotid artery stenting: outcomes, safety, and operational learning curve.
Neurosurgical focus
Jan 1, 2022
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...
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
Dec 31, 2020
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. ...
Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture.
Ultrasonic imaging
Jan 1, 2020
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...
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