AIMC Topic: Computed Tomography Angiography

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Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier.

Medical image analysis Oct 22, 2018
Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose an algorithm that extracts coronary artery centerlines in CCTA using a con...
Contrast Media Radiographic Image Interpretation, Computer-Assisted Netherlands Coronary Vessels Computed Tomography Angiography Humans Neural Networks, Computer Algorithms Retrospective Studies
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Machine-learning integration of CT histogram analysis to evaluate the composition of atherosclerotic plaques: Validation with IB-IVUS.

Journal of cardiovascular computed tomography Oct 21, 2018
BACKGROUND: To determine whether machine learning with histogram analysis of coronary CT angiography (CCTA) yields higher diagnostic performance for coronary plaque characterization than the conventional cut-off method using the median CT number.
Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Multidetector Computed Tomography Plaque, Atherosclerotic Male Predictive Value of Tests Coronary Angiography Humans Ultrasonography, Interventional Machine Learning Retrospective Studies Female Reproducibility of Results Aged Computed Tomography Angiography
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Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR.

The international journal of cardiovascular imaging Jul 30, 2018
To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in cath...
Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Humans Machine Learning Coronary Stenosis Fractional Flow Reserve, Myocardial Cardiac Catheters Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Male Coronary Vessels Middle Aged Multidetector Computed Tomography Severity of Illness Index Computed Tomography Angiography Predictive Value of Tests
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3-D Neural denoising for low-dose Coronary CT Angiography (CCTA).

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 29, 2018
CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. However, it exposes the patient to significant radiation doses, resulting from high image quality requirements and acquisitions at multiple cardiac ph...
Neural Networks, Computer Algorithms Imaging, Three-Dimensional Coronary Angiography Signal-To-Noise Ratio Humans Thorax Computed Tomography Angiography
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Machine learning in cardiac CT: Basic concepts and contemporary data.

Journal of cardiovascular computed tomography Apr 30, 2018
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular ...
Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Vascular Calcification Machine Learning Computed Tomography Angiography Humans Algorithms Prognosis Reproducibility of Results Severity of Illness Index
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Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry.

Journal of cardiovascular computed tomography Apr 30, 2018
INTRODUCTION: Machine learning (ML) is a field in computer science that demonstrated to effectively integrate clinical and imaging data for the creation of prognostic scores. The current study investigated whether a ML score, incorporating only the 1...
Coronary Stenosis Humans Coronary Vessels Machine Learning Multidetector Computed Tomography Plaque, Atherosclerotic Severity of Illness Index Computed Tomography Angiography Risk Factors Algorithms Coronary Angiography Time Factors Prognosis Aged Radiographic Image Interpretation, Computer-Assisted ROC Curve Female Male Registries Predictive Value of Tests Reproducibility of Results Middle Aged Coronary Artery Disease Area Under Curve Risk Assessment Myocardial Infarction
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Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Radiology Apr 10, 2018
Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR) and F...
Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Female Reproducibility of Results Sensitivity and Specificity Male Middle Aged Hemodynamics Predictive Value of Tests Coronary Angiography Hydrodynamics Humans Machine Learning Algorithms Retrospective Studies
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Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Medical image analysis Mar 27, 2018
Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate qu...
Contrast Media Pattern Recognition, Automated Aortic Aneurysm, Abdominal Computed Tomography Angiography Humans Radiographic Image Interpretation, Computer-Assisted Thrombosis Neural Networks, Computer Artifacts
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Automated estimation of image quality for coronary computed tomographic angiography using machine learning.

European radiology Mar 23, 2018
OBJECTIVES: Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA).
Coronary Artery Disease Computed Tomography Angiography Radiographic Image Enhancement Female Aged Male Humans Middle Aged Machine Learning Area Under Curve
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Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

European radiology Feb 23, 2018
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).
Middle Aged Intracranial Aneurysm ROC Curve Aged Predictive Value of Tests Humans Age Factors Anterior Cerebral Artery Aged, 80 and over Models, Biological Decision Making Neural Networks, Computer Young Adult Computed Tomography Angiography Female Adult Cerebral Angiography Risk Factors Male Aneurysm, Ruptured
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