AIMC Topic: Computed Tomography Angiography

Clear Filters Showing 321 to 330 of 492 articles

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

PloS one May 6, 2020
OBJECTIVES: To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation.
Humans Middle Aged Coronary Vessels Female Deep Learning Computed Tomography Angiography Aged Heart Heart Ventricles Male Heart Atria
View on PubMed DOI

Development and validation of machine learning prediction model based on computed tomography angiography-derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study.

European radiology Apr 29, 2020
OBJECTIVES: To build models based on conventional logistic regression (LR) and machine learning (ML) algorithms combining clinical, morphological, and hemodynamic information to predict individual rupture status of unruptured intracranial aneurysms (...
Humans Cerebral Angiography Adult Aneurysm, Ruptured Male Tomography, X-Ray Computed Intracranial Aneurysm Middle Aged Neural Networks, Computer Female Clinical Decision Rules Hemodynamics Adolescent Machine Learning Aged China Logistic Models Computer Simulation Aged, 80 and over Support Vector Machine Retrospective Studies Young Adult Area Under Curve Computed Tomography Angiography
View on PubMed DOI

Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional convolutional neural network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 27, 2020
We propose a fully automated algorithm based on a deep learning framework enabling screening of a coronary computed tomography angiography (CCTA) examination for confident detection of the presence or absence of coronary artery atherosclerosis. The s...
Imaging, Three-Dimensional Coronary Angiography Humans Coronary Artery Disease Neural Networks, Computer Computed Tomography Angiography
View on PubMed DOI

Machine learning volumetry of ischemic brain lesions on CT after thrombectomy-prospective diagnostic accuracy study in ischemic stroke patients.

Neuroradiology Apr 22, 2020
PURPOSE: Ischemic lesion volume (ILV) is an important radiological predictor of functional outcome in patients with anterior circulation stroke. Our aim was to assess the agreement between automated ILV measurements on NCCT using the Brainomix softwa...
Aged Sensitivity and Specificity Male Ischemic Stroke Radiographic Image Interpretation, Computer-Assisted Thrombectomy Computed Tomography Angiography Cerebral Angiography Diffusion Magnetic Resonance Imaging Humans Machine Learning Software Prospective Studies Female
View on PubMed DOI

Diagnostic performance of deep learning-based vascular extraction and stenosis detection technique for coronary artery disease.

The British journal of radiology Mar 25, 2020
OBJECTIVE: To investigate the diagnostic performance of deep learning (DL)-based vascular extraction and stenosis detection technology in assessing coronary artery disease (CAD).
Humans Retrospective Studies Female Aged Sensitivity and Specificity Coronary Angiography Coronary Artery Disease Angiography, Digital Subtraction Computed Tomography Angiography Coronary Stenosis Male Middle Aged Deep Learning ROC Curve Predictive Value of Tests
View on PubMed DOI

Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

European radiology Mar 12, 2020
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Female Aged Male Middle Aged Hemodynamics Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Cardiac Catheterization Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Cohort Studies Coronary Angiography Percutaneous Coronary Intervention Coronary Artery Disease Disease Management
View on PubMed DOI

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...
Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Angiography Humans Coronary Artery Disease Radiographic Image Interpretation, Computer-Assisted Machine Learning Observer Variation Female Retrospective Studies Coronary Vessels Reproducibility of Results Plaque, Atherosclerotic Aged Vascular Calcification Male Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial
View on PubMed DOI

Automated left ventricular myocardium segmentation using 3D deeply supervised attention U-net for coronary computed tomography angiography; CT myocardium segmentation.

Medical physics Feb 29, 2020
PURPOSE: Segmentation of left ventricular myocardium (LVM) in coronary computed tomography angiography (CCTA) is important for diagnosis of cardiovascular diseases. Due to poor image contrast and large variation in intensity and shapes, LVM segmentat...
Deep Learning Imaging, Three-Dimensional Heart Ventricles Supervised Machine Learning Automation Computed Tomography Angiography Humans Tomography, X-Ray Computed
View on PubMed DOI

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 Angiography Radiographic Image Interpretation, Computer-Assisted Registries Humans Plaque, Atherosclerotic Machine Learning Coronary Artery Disease Computed Tomography Angiography Prospective Studies Multidetector Computed Tomography Female Disease Progression Aged Diagnosis, Computer-Assisted Male Time Factors Middle Aged Predictive Value of Tests
View on PubMed DOI

Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning.

European radiology Feb 16, 2020
OBJECTIVES: To take advantage of the deep learning algorithms to detect and calculate clot burden of acute pulmonary embolism (APE) on computed tomographic pulmonary angiography (CTPA).
Heart Ventricles Computed Tomography Angiography Ventricular Function, Right Middle Aged Deep Learning Acute Disease Pulmonary Embolism Reproducibility of Results Aged Adult Sensitivity and Specificity Male Humans Retrospective Studies Female
View on PubMed DOI
Popular Topics
Recent Journals