Regularized sensitivity encoding (SENSE) reconstruction using Bregman iterations.

  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},
  volume={61 1},
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
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