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Reweighted minimization model for MR image reconstruction with split Bregman method

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Abstract

Magnetic resonance (MR) image reconstruction is to get a practicable gray-scale image from few frequency domain coefficients. In this paper, different reweighted minimization models for MR image reconstruction are studied, and a novel model named reweighted wavelet+TV minimization model is proposed. By using split Bregman method, an iteration minimization algorithm for solving this new model is obtained, and its convergence is established. Numerical simulations show that the proposed model and its algorithm are feasible and highly efficient.

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Authors and Affiliations

  1. Department of Mathematics and Systems Science, College of Science, National University of Defense and Technology, Changsha, 410073, China

    Hui Zhang, LiZhi Cheng & JianPing Li

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  1. Hui Zhang
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  2. LiZhi Cheng
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  3. JianPing Li
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Correspondence to Hui Zhang.

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Zhang, H., Cheng, L. & Li, J. Reweighted minimization model for MR image reconstruction with split Bregman method. Sci. China Inf. Sci. 55, 2109–2118 (2012). https://doi.org/10.1007/s11432-011-4328-2

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  • DOI: https://doi.org/10.1007/s11432-011-4328-2

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