Cardiovascular disease remains an integral field on which new research in both the
biomedical and technological fields is based, as it remains the leading cause of mortality …

Heart failure with preserved ejection fraction (HFpEF) is a syndrome defined by the
presence of heart failure symptoms and increased levels of circulating natriuretic peptide …

Background and aims Artificial intelligence (AI) is increasing its role in diagnosis of patients
with suspicious coronary artery disease. The aim of this manuscript is to develop a deep …

Rationale and Objectives To evaluate deep learning (DL)-based optimization algorithm for
low-dose coronary CT angiography (CCTA) image noise reduction and image quality (IQ) …

Background Tricuspid annulus (TA) sizing is essential for planning percutaneous or surgical
tricuspid procedures. According to current guidelines, TA linear dimension should be …

Purpose To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting
hemodynamically significant coronary artery disease (CAD) by using a rest dataset of …

Rationale and objectives To investigate the relationship between the pericoronary adipose
tissue CT mean attenuation (PCAT MA) measurement and image reconstruction parameters …

Fractional flow reserve (FFR) derived from coronary CTA datasets (FFRCT) is a major
advance in cardiovascular imaging that provides critical information to the Heart Team …

Background Deep learning image reconstruction (DLIR) and adaptive statistical iterative
reconstruction-V (ASIR-V) has been used for cardiac computed tomography imaging …

Purpose To optimize image quality and radiation dose of chest CT with respect to various
iterative reconstruction levels, detector collimations and body sizes. Method A Kyoto Kagaku …