ZHAO Di, DU Huiqian, MEI Wenbo, “Hybrid Weighted l1-Total Variation Constrained Reconstruction for MR Image,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 747-752, 2014,
Citation: ZHAO Di, DU Huiqian, MEI Wenbo, “Hybrid Weighted l1-Total Variation Constrained Reconstruction for MR Image,” Chinese Journal of Electronics, vol. 23, no. 4, pp. 747-752, 2014,

Hybrid Weighted l1-Total Variation Constrained Reconstruction for MR Image

Funds:  This work is supported by Natural Science Foundation of China (No.61077022).
  • Received Date: 2013-04-01
  • Rev Recd Date: 2014-02-01
  • Publish Date: 2014-10-05
  • Compressed sensing based Magnetic resonance (MR) image reconstruction can be done by minimizing the sum of least square data fitting item, the Total variation (TV) and l1 norm regularizations. In this paper, inspired by the conventional constrained reconstruction model, we propose a hybrid weighted l1-TV minimization method to reconstruct MR image. We introduce the iterative mechanism to update the weights for l1 and TV norms adaptively. The weights vary at each element of the image matrix according to the presented weights selection strategy. Experiments on Shepp-Logan phantom and practical MR images demonstrate the proposed method can preserve image details and obtain improved reconstruction quality compared to the traditional CS-MRI method and other weighted methods.
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