AIMC Topic: Computed Tomography Angiography

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Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning.

Journal of cardiovascular computed tomography Apr 21, 2019
In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs ...
Computed Tomography Angiography Reproducibility of Results Severity of Illness Index Deep Learning Predictive Value of Tests Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Prognosis
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Deep learning-based image restoration algorithm for coronary CT angiography.

European radiology Apr 8, 2019
OBJECTIVES: The purpose of this study was to compare the image quality of coronary computed tomography angiography (CTA) subjected to deep learning-based image restoration (DLR) method with images subjected to hybrid iterative reconstruction (IR).
Female Aged Aged, 80 and over Adult Humans Algorithms Retrospective Studies Coronary Vessels Radiation Dosage Signal-To-Noise Ratio Multidetector Computed Tomography Computed Tomography Angiography Male Middle Aged Deep Learning Radiographic Image Interpretation, Computer-Assisted
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Machine Learning Using CT-FFR Predicts Proximal Atherosclerotic Plaque Formation Associated With LAD Myocardial Bridging.

JACC. Cardiovascular imaging Mar 13, 2019
Humans Machine Learning Prognosis Retrospective Studies Middle Aged Time Factors Predictive Value of Tests Coronary Angiography Coronary Artery Disease Female Risk Factors Aged Male Fractional Flow Reserve, Myocardial Myocardial Bridging Image Interpretation, Computer-Assisted Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography
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Cycle-consistent adversarial denoising network for multiphase coronary CT angiography.

Medical physics Dec 26, 2018
PURPOSE: In multiphase coronary CT angiography (CTA), a series of CT images are taken at different levels of radiation dose during the examination. Although this reduces the total radiation dose, the image quality during the low-dose phases is signif...
Machine Learning Coronary Vessels Signal-To-Noise Ratio Computed Tomography Angiography Humans
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Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology Dec 20, 2018
BACKGROUND AND PURPOSE: Thrombus characteristics identified on non-contrast CT (NCCT) are potentially associated with recanalization with intravenous (IV) alteplase in patients with acute ischemic stroke (AIS). Our aim was to determine the best radio...
Computed Tomography Angiography Intracranial Thrombosis Middle Aged Case-Control Studies ROC Curve Treatment Outcome Tissue Plasminogen Activator Image Interpretation, Computer-Assisted Neuroimaging Support Vector Machine Stroke Tomography, X-Ray Computed Female Aged Male Humans
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Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

European radiology Dec 6, 2018
OBJECTIVES: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FF...
Diagnosis, Computer-Assisted ROC Curve Coronary Angiography Plaque, Atherosclerotic Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Retrospective Studies Female Male Middle Aged Humans Machine Learning
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A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography.

IEEE transactions on medical imaging Nov 28, 2018
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different management of patients with a coronary artery disease. Therefore, it is crucial to detect and classify the type of coronary artery plaque, as well as to de...
Computed Tomography Angiography Coronary Stenosis Image Processing, Computer-Assisted Coronary Angiography Coronary Vessels Plaque, Atherosclerotic Humans Neural Networks, Computer Algorithms
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Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks.

Medical image analysis Nov 15, 2018
Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiography. Artifacts due to cardiac motion may interfere with detection and diagnosis of coronary artery disease and render subsequent treatment decisions mor...
Humans Neural Networks, Computer Coronary Angiography Supervised Machine Learning Motion Software Algorithms Artifacts Computed Tomography Angiography Cardiac-Gated Imaging Techniques
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Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFR): Impact of iterative and filtered back projection reconstruction techniques.

Journal of cardiovascular computed tomography Oct 26, 2018
BACKGROUND: The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR) has not been investigated. CT-FFR values and processing time of two reconstructio...
Severity of Illness Index Predictive Value of Tests Coronary Stenosis Reproducibility of Results Coronary Angiography Fractional Flow Reserve, Myocardial Radiographic Image Interpretation, Computer-Assisted Aged Male Coronary Artery Disease Middle Aged Workflow Humans Coronary Vessels Machine Learning Computed Tomography Angiography Retrospective Studies Female
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JOURNAL CLUB: Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information.

AJR. American journal of roentgenology Oct 24, 2018
OBJECTIVE: When treatment decisions are being made for patients with acute ischemic stroke, timely and accurate outcome prediction plays an important role. The optimal rehabilitation strategy also relies on long-term outcome predictions. The decision...
Algorithms Demography Decision Trees Biomarkers Predictive Value of Tests Prognosis Humans Tomography, X-Ray Computed Stroke Retrospective Studies Machine Learning Female Brain Ischemia Male Computed Tomography Angiography Middle Aged
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