Fast Regularized Reconstruction of Non-uniformly Subsampled Partial-Fourier Parallel MRI data

W. S. Hoge, Misha E. Kilmer, Carlos Zacarias-Almarcha, Dana H. Brooks
Proc of 2007 IEEE Intl Symp on Biomedical Imaging (ISBI07)
Pages 1012-1015
April 12-15, 2007

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Abstract

We present an adaptation of our previous fast, regularized parallel MRI reconstruction approach (LSQR-Hybrid) to encompass the reconstruction of partial-Fourier data. Reconstructions of partial-Fourier data require a constraint on the signal phase variation in the reconstructed image. Here, we employ a two-parameter Tikhonov regularization formulation to constrain the real and imaginary components separately. A variation of the LSQR-Hybrid algorithm is used to rapidly reconstruct a set of images across the two-dimensional regularization parameter search space. The "best" image available is chosen as the one with the least system error using the most regularization. Results are demonstrated with subsampled parallel MR data acquired on a 1.5T MRI system.

Reference

Hoge WS, Kilmer ME, Zacarias-Almarcha C, Brooks DH. Fast regularized reconstruction of non-uniformly subsampled partial-fourier parallel MRI data. In Proc of 2007 IEEE Intl Symp on Biomedical Imaging (ISBI07). Arlington, VA, USA, 2007;1012-1015.

Bibtex entry

@inProceedings{hoge:ISBI07,
  title          = {Fast Regularized Reconstruction of Non-uniformly Subsampled
                   Partial-Fourier Parallel {MRI} data},                       
  author         = {Hoge, W. Scott and Kilmer, Misha E. and Zacarias-Almarcha, 
                   Carlos and Brooks, Dana H.},                                
  booktitle      = {Proc of 2007 IEEE Intl Symp on Biomedical Imaging          
                   (ISBI07)},                                                  
  pages          = {1012-1015},                                                
  month          = {April 12--15},                                             
  year           = 2007,                                                       
  address        = {Arlington, VA, USA}
}

Grants

NIH U41-RR019703

Copyright Information

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