Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …

The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …

Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data
provides a more thorough characterization of cardiac mechanics than volumetric parameters …

Background Cardiovascular magnetic resonance (CMR) cine displacement encoding with
stimulated echoes (DENSE) measures heart motion by encoding myocardial displacement …

Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR)
imaging enables the assessment of regional myocardial function and is important for …

A CNN based method for cardiac MRI tag tracking was developed and validated. A synthetic
data simulator was created to generate large amounts of training data using natural images …

Advanced cardiac imaging techniques such as cardiovascular magnetic resonance (CMR)
and positron emission tomography (PET) are widely used in clinical practice in patients with …

Strain represents the quantification of regional tissue deformation within a given area.
Myocardial strain has demonstrated considerable utility as an indicator for the assessment of …

Using cine magnetic resonance imaging (cine MRI) images to track cardiac motion helps
users to analyze the myocardial strain, and is of great importance in clinical applications. At …

Background The clinical utility of late gadolinium enhancement (LGE) cardiac MRI is limited
by the lack of standardization, and time-consuming postprocessing. In this work, we tested …