TV Sparsifying MR Image Reconstruction in Compressive Sensing

Yonggui Zhu, Xiaolan Yang

School of Science, Communication University of China.

DOI: 10.4236/jsip.2011.21007                

Abstract

In this paper, we apply alternating minimization method to sparse image reconstruction in compressed sensing. This approach can exactly reconstruct the MR image from under-sampled k-space data, i.e., the partial Fourier data. The convergence analysis of the fast method is also given. Some MR images are employed to test in the numerical experi-ments, and the results demonstrate that our method is very efficient in MRI reconstruction.

Keywords

Compressed Sensing, Magnetic Resonance Image, Total Variation, Image Reconstruction

Conflicts of Interest

The authors declare no conflicts of interest.

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