AIMC Topic: Carotid Artery Diseases
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Deep Learning-Based Carotid Plaque Segmentation from B-Mode Ultrasound Images.
Ultrasound in medicine & biology
Jul 1, 2021
Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid plaque burden and monitoring changes in carotid atherosclerosis in response to medical treatment. Plaque boundary segmentation is required to generate...
Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes.
Circulation research
Jun 10, 2021
Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss and excess rates of cardiovascular morbidity and death. Machine learnin...
Algorithms
Forecasting
Phenotype
Prognosis
Humans
Artificial Intelligence
Machine Learning
Life Style
Aortic Aneurysm
Behavior Therapy
Carotid Artery Diseases
Natural Language Processing
Atherosclerosis
Supervised Machine Learning
Image Interpretation, Computer-Assisted
Risk Assessment
Treatment Outcome
Peripheral Arterial Disease
Automated segmentation of the individual branches of the carotid arteries in contrast-enhanced MR angiography using DeepMedic.
BMC medical imaging
Feb 27, 2021
BACKGROUND: Non-invasive imaging is of interest for tracking the progression of atherosclerosis in the carotid bifurcation, and segmenting this region into its constituent branch arteries is necessary for analyses. The purpose of this study was to va...
Deep morphology aided diagnosis network for segmentation of carotid artery vessel wall and diagnosis of carotid atherosclerosis on black-blood vessel wall MRI.
Medical physics
Oct 14, 2019
PURPOSE: Early detection of carotid atherosclerosis on the vessel wall (VW) magnetic resonance imaging (MRI) (VW-MRI) images can prevent the progression of cardiovascular disease. However, the manual inspection process of the VW-MRI images is cumbers...
Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization.
Current atherosclerosis reports
Jan 25, 2019
PURPOSE OF THE REVIEW: Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue characterization and risk stratification of patients with rheumatoid arthritis are a ...
Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.
Computers in biology and medicine
Aug 20, 2018
PURPOSE OF REVIEW: Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and ...
Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.
Computers in biology and medicine
May 12, 2018
MOTIVATION: The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of dee...
Prediction of persistent hemodynamic depression after carotid angioplasty and stenting using artificial neural network model.
Clinical neurology and neurosurgery
Dec 5, 2017
OBJECTIVES: To assess and compare predictive factors for persistent hemodynamic depression (PHD) after carotid artery angioplasty and stenting (CAS) using artificial neural network (ANN) and multiple logistic regression (MLR) or support vector machin...
A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound.
IEEE journal of biomedical and health informatics
Nov 22, 2016
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 ...
Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.
Journal of neurointerventional surgery
Jun 16, 2025
BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians.
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