Cardiac magnetic resonance (CMR) is an essential clinical tool for the assessment of
cardiovascular disease. Deep learning (DL) has recently revolutionized the field through …

Purpose: To explore the use of three-dimensional patient-specific cardiovascular models
using rapid prototyping techniques (fused deposition modelling) to improve surgical …

Purpose: To evaluate the use of four‐dimensional (4D) velocity‐encoded magnetic
resonance imaging (VEC MRI) for blood flow quantification in patients with semilunar valve …

Purpose To develop and validate a deep learning‐based reconstruction framework for
highly accelerated two‐dimensional (2D) phase contrast (PC‐MRI) data with accurate and …

Cardiac computational models, individually personalized, can provide clinicians with useful
diagnostic information and aid in treatment planning. A major bottleneck in this process can …

Patient-specific models become increasingly important in cardiovascular research as they
allow prediction of surgical procedures. While the left ventricular outflow profile is an …

The goal of this study is to evaluate whether NT-proBNP plasma levels may help as a
screening biomarker for monitoring right ventricular dilatation, pulmonary regurgitation and …

Phase‐contrast magnetic resonance imaging is subject to numerous sources of error, which
decrease clinical confidence in the reported measures. This work outlines how stationary …

Heart failure (HF) results from structural or functional cardiac disorders that impair the ability
of the ventricle (s) to fill with and/or eject blood. The presentation of pediatric HF is diverse …

Las cardiopatías congénitas engloban aquellas alteraciones del corazón y grandes vasos
que se originan antes del nacimiento. Se estima que se presentan entre 8 y 10 casos por …