- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
International Journal of Biomedical Imaging
Volume 2012 (2012), Article ID 864827, 6 pages
Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods
1Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
2Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
3Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
4Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
5Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
6Department of Cancer Biology, Vanderbilt University, Nashville, TN 37232, USA
Received 25 July 2011; Revised 25 October 2011; Accepted 31 October 2011
Academic Editor: Yibin Zheng
Copyright © 2012 David S. Smith et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Akcakaya, S. Nam, P. Hu et al., “Compressed sensing with wavelet domain dependencies for coronary MRI: a retrospective study,” IEEE Transactions on Medical Imaging, vol. 30, no. 5, pp. 1090–1099, 2011.
- J. P. Haldar, D. Hernando, and Z.-P. Liang, “Compressed-Sensing MRI With Random Encoding,” IEEE Transactions on Medical Imaging, vol. 30, no. 4, pp. 893–903, 2011.
- R. Otazo, D. Kim, L. Axel, and D. K. Sodickson, “Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI,” Magnetic Resonance in Medicine, vol. 64, no. 3, pp. 767–776, 2010.
- B. Zhao, J. P. Haldar, C. Brinegar, and Z. P. Liang, “Low rank matrix recovery for real-time cardiac MRI,” in Proceedings of the 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI '10), pp. 996–999, Rotterdam, The Netherlands, April 2010.
- M. Lustig, D. Donoho, and J. M. Pauly, “Sparse MRI: the application of compressed sensing for rapid MR imaging,” Magnetic Resonance in Medicine, vol. 58, no. 6, pp. 1182–1195, 2007.
- M. S. Hansen, D. Atkinson, and T. S. Sorensen, “Cartesian SENSE and k-t SENSE reconstruction using commodity graphics hardware,” Magnetic Resonance in Medicine, vol. 59, no. 3, pp. 463–468, 2008.
- T. S. Sorensen, T. Schaeffter, K. O. Noe, and M. S. Hansen, “Accelerating the nonequispaced fast fourier transform on commodity graphics hardware,” IEEE Transactions on Medical Imaging, vol. 27, no. 4, Article ID 4359078, pp. 538–547, 2008.
- S. S. Stone, J. P. Haldar, S. C. Tsao, W. M. W. Hwu, B. P. Sutton, and Z. P. Liang, “Accelerating advanced MRI reconstructions on GPUs,” Journal of Parallel and Distributed Computing, vol. 68, no. 10, pp. 1307–1318, 2008.
- X. Jia, Y. Lou, R. Li, W. Y. Song, and S. B. Jiang, “GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation,” Medical Physics, vol. 37, no. 4, pp. 1757–1760, 2010.
- S. S. Chen, D. L. Donoho, and M. A. Saunders, “Atomic decomposition by basis pursuit,” The SIAM Journal on Scientific Computing, vol. 20, no. 1, pp. 33–61, 1998.
- S. J. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, “An interior-point method for large-scale ℓ1-regularized least squares,” IEEE Journal on Selected Topics in Signal Processing, vol. 1, no. 4, pp. 606–617, 2007.
- I. Daubechies, M. Defrise, and C. de Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Communications on Pure and Applied Mathematics, vol. 57, no. 11, pp. 1413–1457, 2004.
- E. Hale, W. Yin, and Y. Zhang, “Fixed-point continuation for l1-minimization: methodology and convergence,” Tech. Rep. TR07-07, Department of Computational and Applied Mathematics, Rice University, Houston, Tex, USA, 2007.
- E. van den Berg and M. P. Friedlander, “Probing the pareto frontier for basis pursuit solutions,” The SIAM Journal on Scientific Computing, vol. 31, no. 2, pp. 890–912, 2008.
- M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE Journal on Selected Topics in Signal Processing, vol. 1, no. 4, pp. 586–597, 2007.
- T. Goldstein and S. Osher, “The split Bregman methods for L1 regularized problems,” The SIAM Journal on Imaging Sciences, vol. 2, pp. 323–343, 2009.