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E. T. Hale, W. Yin and Y. Zhang, “A Fixed-Point Continuation for l1?regularization with Application to Compressed Sensing,” Rice University CAAM Technical Report TR07-07, 2007, pp. 1-45.

has been cited by the following article:

• TITLE: TV Sparsifying MR Image Reconstruction in Compressive Sensing

  AUTHORS: Yonggui Zhu, Xiaolan Yang

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

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.2 No.1, February 24, 2011

  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.