Purpose Highly trained athletes have an increased risk of atrial arrhythmias. Atrial geometrical and functional remodeling may be the underlying substrate. We analyze and relate atrial size, deformation and performance ...

We propose a technique for myocardial motion estimation based on image registration using both B-mode echocardiographic images and tissue Doppler sequences acquired interleaved. The velocity field is modeled continuously ...

Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively ...

This thesis focuses on the development of machine learning tools to better characterize the cardiac anatomy and function in the context of heart failure, and in particular their extension to consider multiple parameters ...

Diagnosis through imaging generally requires the combination of several modalities. Algorithms for data fusion allow merging information from different sources, mostly combining all images in a single step. In contrast, ...

This paper presents a new registration algorithm, called Temporal Di eomorphic Free Form Deformation (TDFFD), and its application to motion and strain quanti cation from a sequence of 3D ultrasound (US) images. The originality ...