Journal
MAGNETIC RESONANCE IN MEDICINE
Volume 68, Issue 1, Pages 41-53Publisher
WILEY
DOI: 10.1002/mrm.23197
Keywords
compressed sensing; dynamic MRI; k-t iterative support detection; partially known support; truncated l1 minimization
Funding
- UWM Research Foundation
- National Science Foundation [CBET-0846514]
- Lynde and Harry Bradley Foundation
- National Institute of Health [R01EB00615]
- National Nature Science Foundation of China [61102043]
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Compressed sensing (CS) has been used in dynamic cardiac MRI to reduce the data acquisition time. The sparseness of the dynamic image series in the spatial- and temporal-frequency (x-f) domain has been exploited in existing works. In this article, we propose a new k-t iterative support detection (k-t ISD) method to improve the CS reconstruction for dynamic cardiac MRI by incorporating additional information on the support of the dynamic image in x-f space based on the theory of CS with partially known support. The proposed method uses an iterative procedure for alternating between image reconstruction and support detection in x-f space. At each iteration, a truncated l1 minimization is applied to obtain the reconstructed image in x-f space using the support information from the previous iteration. Subsequently, by thresholding the reconstruction, we update the support information to be used in the next iteration. Experimental results demonstrate that the proposed k-t ISD method improves the reconstruction quality of dynamic cardiac MRI over the basic CS method in which support information is not exploited. Magn Reson Med, 2012. (c) 2011 Wiley Periodicals, Inc.
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