A kernel method for higher temporal resolution MRI using the partial separability (PS) model

A kernel method for higher temporal resolution MRI using the partial separability (PS) model AbstractThe partial separability (PS) model for spatiotemporal signals has been exploited effectively for sparse (k, t)-space sampling in dynamic magnetic resonance imaging (MRI). However, the training data for defining the temporal subspace is reordered by using a projection strategy in the conventional PS model-based method, which results in a suboptimal temporal resolution imaging. To address this issue, a kernel method was presented in this work to reorder the training data to realize a higher temporal resolution MRI. Numerical simulation results show that the MRI temporal resolution could be further improved and the dynamic change of motion object could be accurately captured by the proposed method. In vivo cardiac cine MRI results demonstrate that the proposed method can reconstruct better MR images with higher temporal resolution (up to 8.4 ms per snapshot). This study may find use in ultra-high resolution dynamic MRI. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biomedical Engineering / Biomedizinische Technik de Gruyter

A kernel method for higher temporal resolution MRI using the partial separability (PS) model

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Publisher
De Gruyter
Copyright
©2016 Walter de Gruyter GmbH, Berlin/Boston
ISSN
1862-278X
eISSN
1862-278X
D.O.I.
10.1515/bmt-2015-0057
Publisher site
See Article on Publisher Site

Abstract

AbstractThe partial separability (PS) model for spatiotemporal signals has been exploited effectively for sparse (k, t)-space sampling in dynamic magnetic resonance imaging (MRI). However, the training data for defining the temporal subspace is reordered by using a projection strategy in the conventional PS model-based method, which results in a suboptimal temporal resolution imaging. To address this issue, a kernel method was presented in this work to reorder the training data to realize a higher temporal resolution MRI. Numerical simulation results show that the MRI temporal resolution could be further improved and the dynamic change of motion object could be accurately captured by the proposed method. In vivo cardiac cine MRI results demonstrate that the proposed method can reconstruct better MR images with higher temporal resolution (up to 8.4 ms per snapshot). This study may find use in ultra-high resolution dynamic MRI.

Journal

Biomedical Engineering / Biomedizinische Technikde Gruyter

Published: Aug 1, 2016

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