With heart and cardiovascular diseases continually challenging healthcare systems
worldwide, translating basic research on cardiac (patho) physiology into clinical care is …

Multi-modality cardiac imaging plays a key role in the management of patients with
cardiovascular diseases. It allows a combination of complementary anatomical …

Cardiac motion estimation and segmentation play important roles in quantitatively assessing
cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel …

We introduce a strategy for learning image registration without acquired imaging data,
producing powerful networks agnostic to contrast introduced by magnetic resonance …

In this paper we present a benchmarking framework for the validation of cardiac motion
analysis algorithms. The reported methods are the response to an open challenge that was …

Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional
myocardium deformation and cardiac strain estimation. However, this technique has not …

Whole heart segmentation from magnetic resonance imaging or computed tomography is a
prerequisite for many clinical applications. Since manual delineation can be tedious and …

Motion estimation of cardiac MRI videos is crucial for the evaluation of human heart anatomy
and function. Recent researches show promising results with deep learning-based methods …

An unresolved issue in patients with diastolic dysfunction is that the estimation of myocardial
stiffness cannot be decoupled from diastolic residual active tension (AT) because of the …

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