Publication:
High-Resolution Dynamic Cardiac MRI on Small Animals Using Reconstruction Based on Split Bregman Methodology

Loading...
Thumbnail Image
Identifiers
ISSN: 1082-3654
ISBN: 978-1-4673-0118-3
Publication date
2011
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Ieee - The Institute Of Electrical And Electronics Engineers, Inc
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
Dynamic cardiac magnetic resonance imaging in small animals is an important tool in the study of cardiovascular diseases. The reduction of the long acquisition times required for cardiovascular applications is crucial to achieve good spatiotemporal resolution and signal-to-noise ratio. Nowadays there are many acceleration techniques which can reduce acquisition time, including compressed sensing technique. Compressed sensing allows image reconstruction from undersampled data, by means of a non linear reconstruction which minimizes the total variation of the image. The recently appeared Split Bregman methodology has proved to be more computationally efficient to solve this problem than classic optimization methods. In the case of dynamic magnetic resonance imaging, compressed sensing can exploit time sparsity by the minimization of total variation across both space and time. In this work, we propose and validate the Split Bregman method to minimize spatial and time total variation, and apply this method to accelerate cardiac cine acquisitions in rats. We found that applying a quasi-random variable density pattern along the phase-encoding direction, accelerations up to a factor 5 are possible with low error. In the future, we expect to obtain higher accelerations using spatiotemporal undersampling.
Description
Proceedings of: 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). Valencia, Spain, 23-29 October 2011
Keywords
Biomedical MRI, Cardiovascular system, Compressed sensing, Diseases, Image coding, Image reconstruction, Image sampling, Optimisation, Phase coding, Spatiotemporal phenomena, Variational techniques
Bibliographic citation
2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC): Valencia, Spain. 23-29 October 2011 (2011). IEEE, 3462-3464.