AIMC Topic: Plaque, Atherosclerotic
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Ischemia and outcome prediction by cardiac CT based machine learning.
The international journal of cardiovascular imaging
Jul 4, 2020
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for card...
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Computed Tomography Angiography
Heart Disease Risk Factors
Coronary Vessels
Plaque, Atherosclerotic
Vascular Calcification
Prognosis
Reproducibility of Results
Risk Assessment
Severity of Illness Index
Humans
Machine Learning
From CT to artificial intelligence for complex assessment of plaque-associated risk.
The international journal of cardiovascular imaging
Jul 2, 2020
The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust inform...
Reproducibility of Results
Risk Assessment
Severity of Illness Index
Predictive Value of Tests
Humans
Machine Learning
Prognosis
Coronary Vessels
Rupture, Spontaneous
Plaque, Atherosclerotic
Computed Tomography Angiography
Coronary Stenosis
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Heart Disease Risk Factors
The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFR) values.
The international journal of cardiovascular imaging
Mar 4, 2020
To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative reconstruction, ADMIRE) on machine learning-based coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) measurements compared...
Coronary Artery Disease
Observer Variation
Coronary Vessels
Plaque, Atherosclerotic
Severity of Illness Index
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Vascular Calcification
Computed Tomography Angiography
Coronary Stenosis
Fractional Flow Reserve, Myocardial
Humans
Machine Learning
Retrospective Studies
Female
Reproducibility of Results
Aged
Male
Middle Aged
Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.
Journal of the American Heart Association
Feb 22, 2020
Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed to...
Coronary Artery Disease
Machine Learning
Multidetector Computed Tomography
Prospective Studies
Plaque, Atherosclerotic
Female
Predictive Value of Tests
Computed Tomography Angiography
Aged
Coronary Angiography
Disease Progression
Radiographic Image Interpretation, Computer-Assisted
Male
Diagnosis, Computer-Assisted
Humans
Registries
Time Factors
Middle Aged
Detecting vulnerable plaque with vulnerability index based on convolutional neural networks.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 19, 2020
Plaque rupture and subsequent thrombosis are major processes of acute cardiovascular events. The Vulnerability Index is a very important indicator of whether a plaque is ruptured, and these easily ruptured or fragile plaques can be detected early. Th...
Fully automated plaque characterization in intravascular OCT images using hybrid convolutional and lumen morphology features.
Scientific reports
Feb 13, 2020
For intravascular OCT (IVOCT) images, we developed an automated atherosclerotic plaque characterization method that used a hybrid learning approach, which combined deep-learning convolutional and hand-crafted, lumen morphological features. Processing...
Bimodal Automated Carotid Ultrasound Segmentation Using Geometrically Constrained Deep Neural Networks.
IEEE journal of biomedical and health informatics
Jan 9, 2020
For asymptomatic patients suffering from carotid stenosis, the assessment of plaque morphology is an important clinical task which allows monitoring of the risk of plaque rupture and future incidents of stroke. Ultrasound Imaging provides a safe and ...
Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation.
Artificial intelligence in medicine
Dec 31, 2019
BACKGROUND AND OBJECTIVE: The measurement of carotid intima media thickness (CIMT) in ultrasound images can be used to detect the presence of atherosclerotic plaques. Usually, the CIMT estimation strategy is semi-automatic, since it requires: (1) a m...
Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study.
European radiology
Oct 18, 2019
OBJECTIVE: To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts.
Automated Detection of Vulnerable Plaque for Intravascular Optical Coherence Tomography Images.
Cardiovascular engineering and technology
Sep 18, 2019
PURPOSE: Vulnerable plaque detection is important to acute coronary syndrome (ACS) diagnosis. In recent years, intravascular optical coherence tomography (IVOCT) imaging has been used for vulnerable plaque detection. Current automated detection metho...
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