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L. He, T. C. Chang, S. Osher, T. Fang and P. Speier, “MR image reconstruction by using the iterative refinement method and nonlinear inverse scale space methods,” UCLA CAM Report, 2006,06-35.

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.