MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI.

ABSTRACT: 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 understanding and analyzing cardiovascular disease. However, 3D cardiac motion estimation is challenging because the acquired cine CMR images are usually 2D slices which limit the accurate estimation of through-plane motion. To address this problem, we propose a novel multi-view motion estimation network (MulViMotion), which integrates 2D cine CMR images acquired in short-axis and long-axis planes to learn a consistent 3D motion field of the heart. In the proposed method, a hybrid 2D/3D network is built to generate dense 3D motion fields by learning fused representations from multi-view images. To ensure that the motion estimat

SUBMITTER: Meng Q 

PROVIDER: S-EPMC7613225 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature