Regularized sensitivity encoding (SENSE) reconstruction using Bregman iterations.

@article{Liu2009RegularizedSE,
  title={Regularized sensitivity encoding (SENSE) reconstruction using Bregman iterations.},
  author={Bo Liu and Kevin V King and Michael Steckner and Jun Xie and Jinhua Sheng and Leslie Ying},
  journal={Magnetic resonance in medicine},
  year={2009},
  volume={61 1},
  pages={145-52}
}
In parallel imaging, the signal-to-noise ratio (SNR) of sensitivity encoding (SENSE) reconstruction is usually degraded by the ill-conditioning problem, which becomes especially serious at large acceleration factors. Existing regularization methods have been shown to alleviate the problem. However, they usually suffer from image artifacts at high acceleration factors due to the large data inconsistency resulting from heavy regularization. In this paper, we propose Bregman iteration for SENSE… CONTINUE READING
Highly Cited
This paper has 316 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.
48 Citations
44 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 48 extracted citations

317 Citations

050100'10'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 317 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 44 references

Bregman iterative algorithms for compressed sensing and related problems

  • W Yin, S Osher, J Darbon, D. Goldfarb
  • SIAM J Imaging Sciences
  • 2008

Parallel imaging in clinical

  • SO Schoenberg, O Dietrich, MF Reiser, E Adalsteinsson, M Aksoy, editors
  • MR applications. Berlin: Springer Verlag;
  • 2007

Similar Papers

Loading similar papers…