Sparsity-Promoting Calibration for GRAPPA Accelerated Parallel MRI Reconstruction
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Adalsteinsson_Sparsity-promoting.pdf
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Author(s)
Weller, Daniel S.
Polimeni, Jonathan R.
Grady, Leo
Wald, Lawrence L.
Adalsteinsson, Elfar
Goyal, Vivek K.
Date Issued
June 2013
Journal
IEEE Transactions on Medical Imaging
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Weller, Daniel S., Jonathan R. Polimeni, Leo Grady, Lawrence L. Wald, Elfar Adalsteinsson, and Vivek K. Goyal. “Sparsity-Promoting Calibration for GRAPPA Accelerated Parallel MRI Reconstruction.” IEEE Trans. Med. Imaging 32, no. 7 (n.d.): 1325–1335.
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Author's final manuscript
Abstract
The amount of calibration data needed to produce images of adequate quality can prevent auto-calibrating parallel imaging reconstruction methods like generalized autocalibrating partially parallel acquisitions (GRAPPA) from achieving a high total acceleration factor. To improve the quality of calibration when the number of auto-calibration signal (ACS) lines is restricted, we propose a sparsity-promoting regularized calibration method that finds a GRAPPA kernel consistent with the ACS fit equations that yields jointly sparse reconstructed coil channel images. Several experiments evaluate the performance of the proposed method relative to unregularized and existing regularized calibration methods for both low-quality and underdetermined fits from the ACS lines. These experiments demonstrate that the proposed method, like other regularization methods, is capable of mitigating noise amplification, and in addition, the proposed method is particularly effective at minimizing coherent aliasing artifacts caused by poor kernel calibration in real data. Using the proposed method, we can increase the total achievable acceleration while reducing degradation of the reconstructed image better than existing regularized calibration methods.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
https://doi.org/10.1109/TMI.2013.2256923
