AIMC Topic: Coronary Vessels

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Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

European heart journal Jan 14, 2020
AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and t...
Humans Machine Learning Prospective Studies Female Male Coronary Artery Disease Calcium Coronary Vessels Multidetector Computed Tomography Computed Tomography Angiography Middle Aged ROC Curve Predictive Value of Tests Coronary Angiography Registries
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Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets.

Journal of biomedical optics Oct 1, 2019
We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features. We incorporated features developed in previous st...
Image Interpretation, Computer-Assisted Coronary Vessels Endovascular Procedures Plaque, Atherosclerotic Humans Machine Learning Algorithms Databases, Factual Support Vector Machine Tomography, Optical Coherence Coronary Artery Disease
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Optical Coherence Tomography Vulnerable Plaque Segmentation Based on Deep Residual U-Net.

Reviews in cardiovascular medicine Sep 30, 2019
Automatic and accurate segmentation of intravascular optical coherence tomography imagery is of great importance in computer-aided diagnosis and in treatment of cardiovascular diseases. However, this task has not been well addressed for two reasons. ...
Humans Plaque, Atherosclerotic Tomography, Optical Coherence Entropy Prognosis Coronary Artery Disease Reproducibility of Results Image Interpretation, Computer-Assisted Deep Learning Coronary Vessels Predictive Value of Tests Rupture, Spontaneous
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Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.

European heart journal Jun 21, 2019
Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within th...
Artificial Intelligence Machine Learning Algorithms Sensitivity and Specificity Cardiovascular Diseases Humans Neural Networks, Computer Coronary Vessels Tomography, Emission-Computed, Single-Photon Computed Tomography Angiography Cardiac Imaging Techniques Echocardiography Electrocardiography Positron Emission Tomography Computed Tomography Calcium Heart Failure
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Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Journal of the American Heart Association Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
Coronary Stenosis Fractional Flow Reserve, Myocardial Retrospective Studies Female Male Middle Aged Severity of Illness Index ROC Curve Imaging, Three-Dimensional Coronary Angiography Coronary Vessels Humans Machine Learning Algorithms
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Coronary Artery Segmentation by Deep Learning Neural Networks on Computed Tomographic Coronary Angiographic Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Coronary artery lumen delineation, to localize and grade stenosis, is an important but tedious and challenging task for coronary heart disease evaluation. Deep learning has recently been successful applied to many applications, including medical imag...
Coronary Vessels Computed Tomography Angiography Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Circulation. Cardiovascular imaging Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Humans Prospective Studies Europe Coronary Vessels Male Asia Middle Aged Predictive Value of Tests Retrospective Studies Computed Tomography Angiography Severity of Illness Index Coronary Angiography Female Coronary Stenosis Deep Learning Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Fractional Flow Reserve, Myocardial United States Coronary Artery Disease Aged
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Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.

IEEE transactions on medical imaging Feb 1, 2018
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus enable identifi...
Lung Neoplasms Calcinosis Aortic Valve Stenosis Aortic Valve Coronary Artery Disease Coronary Vessels Radiography, Thoracic Neural Networks, Computer Algorithms Tomography, X-Ray Computed Aged Middle Aged Humans
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Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

Journal of biomedical optics Dec 1, 2017
Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback sc...
Linear Models Coronary Vessels Endovascular Procedures Aged Humans Neural Networks, Computer Male Algorithms Middle Aged Female Tomography, Optical Coherence Image Interpretation, Computer-Assisted
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Association of Multiorgan Computed Tomographic Phenomap With Adverse Cardiovascular Health Outcomes: The Framingham Heart Study.

JAMA cardiology Nov 1, 2017
IMPORTANCE: Increased ability to quantify anatomical phenotypes across multiple organs provides the opportunity to assess their cumulative ability to identify individuals at greatest susceptibility for adverse outcomes.
Proof of Concept Study Risk Assessment Cohort Studies Aged Intra-Abdominal Fat Heart Valves United States Humans Adult Mortality Longitudinal Studies Aorta Phenotype Liver Male Vascular Calcification Cause of Death Tomography, X-Ray Computed Muscle, Skeletal Cardiovascular Diseases Female Stroke Unsupervised Machine Learning Middle Aged Myocardial Infarction Adipose Tissue Coronary Vessels Principal Component Analysis
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