Coronary Angiography
Showing 421 to 430 of 435 articles
Machine Learning and Deep Neural Networks Applications in Coronary Flow Assessment: The Case of Computed Tomography Fractional Flow Reserve.
Journal of thoracic imaging
May 1, 2020
Coronary computed tomography angiography (cCTA) is a reliable and clinically proven method for the evaluation of coronary artery disease. cCTA data sets can be used to derive fractional flow reserve (FFR) as CT-FFR. This method has respectable result...
Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography.
European heart journal. Cardiovascular Imaging
Apr 1, 2020
AIMS: Although deep-learning algorithms have been used to compute fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA), no study has achieved 'fully automated' (i.e. free from human input) FFR calculation using deep-lear...
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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...
Virtual fractional flow reserve and virtual coronary stent guided percutaneous coronary intervention.
Cardiology journal
Jan 1, 2020
Detection and Classification of Chronic Total Occlusion lesions using Deep Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Cardiovascular disease (CVD) is one of the diseases with the highest mortality rate in modern society, while chronic total occlusion (CTO) is the initial factor that influences the success rate of percutaneous coronary intervention (PCI), which is on...
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...
Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study.
Journal of computer assisted tomography
Jan 1, 2019
OBJECTIVE: Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusio...
Computed Tomography Angiography
Cardiac-Gated Imaging Techniques
Iopamidol
Coronary Artery Disease
Feasibility Studies
Knowledge Bases
Multidetector Computed Tomography
Female
Aged
Male
Middle Aged
Hemodynamics
Contrast Media
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Exercise Test
Humans
Algorithms
Retrospective Studies
A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.
The Journal of invasive cardiology
Jan 1, 2019
OBJECTIVES: Cancer has been proposed as a cardiovascular risk factor. We aimed to assess the cardiovascular risk profile and coronary angiography (CA) findings of cancer patients and compare them to those of patients without cancer.
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Logistic Models
Age Factors
Coronary Angiography
Coronary Artery Disease
Reference Values
Sex Factors
Academic Medical Centers
Multivariate Analysis
Propensity Score
Male
Risk Assessment
Humans
Neoplasms
Prevalence
Case-Control Studies
Machine Learning
Retrospective Studies
Female
Texas
Aged
Cancer Care Facilities
Aged, 80 and over
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...
Deep Learning
United States
Europe
Predictive Value of Tests
Coronary Angiography
Aged
Male
Middle Aged
Severity of Illness Index
Computed Tomography Angiography
Coronary Stenosis
Fractional Flow Reserve, Myocardial
Humans
Radiographic Image Interpretation, Computer-Assisted
Prospective Studies
Coronary Artery Disease
Retrospective Studies
Coronary Vessels
Female
Asia
Reproducibility of Results
[Automated Classification of Calcification and Stent on Computed Tomography Coronary Angiography Using Deep Learning].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2018
In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aide...
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