Background Visual and histogram-based assessments of coronary CT angiography have limited accuracy in the identification of advanced lesions. Radiomics-based machine learning (ML) could provide a more accurate tool. Purpose To compare the diagnostic ...
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often leads to a heart attack. It annually causes millions of deaths and billions of dollars in financial losses worldwide. Angiography, which is invasive and risky, is...
Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine learning to develop a model of vessel features to discriminate between patients with and without subs...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 14, 2019
Cardiac motion artifacts frequently reduce the interpretability of coronary computed tomography angiography (CCTA) images and potentially lead to misinterpretations or preclude the diagnosis of coronary artery disease (CAD). In this paper, a novel mo...
Circulation journal : official journal of the Japanese Circulation Society
Jun 8, 2019
BACKGROUND: This study evaluated the diagnostic capability of on-site coronary computed tomography-derived computational fractional flow reserve (CT-FFR) determinations for detecting coronary artery disease (CAD), as assessed by invasive fractional f...
AJR. American journal of roentgenology
Apr 30, 2019
Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR). However, attenuation values vary according to the tube voltage used, and i...
Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in the prediction of mortality in acute coronary syndrome (ACS). The value of ML and extensive clinical data was analyzed in a retrospective registry stud...
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 ...
OBJECTIVES: The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFR algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically s...
PURPOSE: The purpose of this study is to introduce and evaluate the mixed structure regularization (MSR) approach for a deep sparse autoencoder aimed at unsupervised abnormality detection in medical images. Unsupervised abnormality detection based on...
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