AIMC Topic: Carotid Arteries
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Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.
Ultraschall in der Medizin (Stuttgart, Germany : 1980)
Dec 19, 2023
PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of...
Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.
Hypertension (Dallas, Tex. : 1979)
Oct 30, 2023
BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys i...
A machine learning approach for computation of cardiovascular intrinsic frequencies.
PloS one
Oct 26, 2023
Analysis of cardiovascular waveforms provides valuable clinical information about the state of health and disease. The intrinsic frequency (IF) method is a recently introduced framework that uses a single arterial pressure waveform to extract physiol...
Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.
Artificial intelligence in medicine
Sep 20, 2023
Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are prone to...
Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications.
Physics in medicine and biology
Jul 24, 2023
. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniques have shown great promise as a low-cost and non-invasive tool to enable localized maps of arterial...
Accelerated Measurement of Carotid Plaque Volume Using Artificial Intelligence Enhanced 3D Ultrasound.
Annals of vascular surgery
Jun 22, 2023
BACKGROUND: Carotid plaque volume (CPV) can be measured by 3D ultrasound and may be a better predictor of stroke than stenosis, but analysis time limits clinical utility. This study tested the accuracy, reproducibility, and time saved of using an art...
Deep-learning-assisted and GPU-accelerated vector Doppler imaging with aliasing-resistant velocity estimation.
Ultrasonics
May 24, 2023
Vector flow imaging is a diagnostic ultrasound modality that is suited for the visualization of complex blood flow dynamics. One popular way of realizing vector flow imaging at high frame rates over 1000 fps is to apply multi-angle vector Doppler est...
3D Ultrasound Reconstructions of the Carotid Artery and Thyroid Gland Using Artificial-Intelligence-Based Automatic Segmentation-Qualitative and Quantitative Evaluation of the Segmentation Results via Comparison with CT Angiography.
Sensors (Basel, Switzerland)
Mar 3, 2023
The aim of this study was to evaluate the feasibility of a noninvasive and low-operator-dependent imaging method for carotid-artery-stenosis diagnosis. A previously developed prototype for 3D ultrasound scans based on a standard ultrasound machine an...
Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.
European radiology
Dec 13, 2022
OBJECTIVES: Accurate detection of carotid plaque using ultrasound (US) is essential for preventing stroke. However, the diagnostic performance of junior radiologists (with approximately 1 year of experience in carotid US evaluation) is relatively poo...
Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.
Computers in biology and medicine
Sep 10, 2022
OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...
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