Paper
9 March 2010 Accurate 2D cardiac motion tracking using scattered data fitting incorporating phase information from MRI
Hui Wang, Amir A. Amini
Author Affiliations +
Abstract
Magnetic resonance imaging has been widely used in measuring cardiac motion due to its ability to non-invasively alter tissue magnetization and produce visible tags in the deforming tissue. Additionally, phase from spectral peaks of tagged images has been used for estimation of myocardial motion. In this paper, we propose integration of displacement information obtained from tagged images in the spatial domain with displacement information obtained from spectral peaks in the frequency domain in order to improve the accuracy of motion tracking. B-splines have been used extensively in temporal registration and reconstruction of myocardial deformations due to their ability to conform to local deformations while enforcing continuity. By considering the real tag intersections (in the spatial domain) and virtual tag intersections (from the frequency domain) as scattered data, multilevel B-splines (MBS) can result in accurate and fast approximations without the need to specify the control point locations explicitly. The accuracy and the effectiveness of the proposed method has been validated by using simulated data from the 13-parameter kinematic model of Arts et al.1 and by using in vivo canine data.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hui Wang and Amir A. Amini "Accurate 2D cardiac motion tracking using scattered data fitting incorporating phase information from MRI", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 76260M (9 March 2010); https://doi.org/10.1117/12.846390
Lens.org Logo
CITATIONS
Cited by 7 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Magnetic resonance imaging

Data modeling

Motion models

Tissues

Fourier transforms

Heart

In vivo imaging

Back to Top