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A Fast Method for Reconstruction of Total-Variation MR Images With a Periodic Boundary Condition

Yonggui Zhu Communication University of China Yuying Shi North China Electric Power University

Numerical Analysis and Scientific Computing mathscidoc:1702.25077

IEEE Signal Processing Letters, 20, (3), 291-294, 2013.4
We use a small positive parameter to change the totalvariation function for unconstrainedMRimage reconstruction to a strictly convex perturbed function. Bregman iteration is applied to solve the modified total-variation MR image (TVMRI) reconstruction problem. A lagged diffusivity fixed-point algorithm is applied to solve the minimization problem in the Bregman iteration. We use the periodic boundary condition and a Fourier transform to accelerate TVMRI reconstruction.RealMR images are used to test the approach in numerical experiments. The experimental results demonstrate that the proposed method is very efficient for TVMRI reconstruction.
Bregman iterative regularization; compressed sensing; fixed-point iteration; total variation.
[ Download ] [ 2017-02-10 02:44:37 uploaded by ygzhu ] [ 859 downloads ] [ 0 comments ] 
@inproceedings{yonggui2013a,
  title={A Fast Method for Reconstruction of Total-Variation MR Images With a Periodic Boundary Condition},
  author={Yonggui Zhu, and Yuying Shi},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170210024437412697420},
  booktitle={IEEE Signal Processing Letters},
  volume={20},
  number={3},
  pages={291-294},
  year={2013},
}
Yonggui Zhu, and Yuying Shi. A Fast Method for Reconstruction of Total-Variation MR Images With a Periodic Boundary Condition. 2013. Vol. 20. In IEEE Signal Processing Letters. pp.291-294. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20170210024437412697420.
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