DEFINING SUB-REGIONS IN LOCALLY SPARSIFIED COMPRESSIVE SENSING MRI

Fuleah A.Razzaq, Shady Mohamed, Asim Bhatti, Saeid Nahavandi

References

  1. [1] M. Lustig, D. Donoho, and J. Pauly, “Sparse mri: Theapplication of compressed sensing for rapid mr imag-ing,” Magnetic Resonance in Medicine, vol. 58, no. 6,pp. 1182–1195, 2007.
  2. [2] G. Marseille, R. De Beer, M. Fuderer, A. Mehlkopf,and D. Van Ormondt, “Nonuniform phase-encode dis-6 Conclusion365tributions for mri scan time reduction,” Journal ofmagnetic resonance. Series B, vol. 111, no. 1, p. 70,1996.
  3. [3] E. Yeh, C. McKenzie, M. Ohliger, and D. Sodickson,“3parallel magnetic resonance imaging with adap-tive radius in k-space (pars): Constrained image re-construction using k-space locality in radiofrequencycoil encoded data,” Magnetic resonance in medicine,vol. 53, no. 6, pp. 1383–1392, 2005.
  4. [4] K. Pruessmann, M. Weiger, M. Scheidegger, andP. Boesiger, “Sense: sensitivity encoding for fast mri,”Magnetic Resonance in Medicine, vol. 42, no. 5, pp.952–962, 1999.
  5. [5] M. Griswold, P. Jakob, R. Heidemann, M. Nittka,V. Jellus, J. Wang, B. Kiefer, and A. Haase, “Gen-eralized autocalibrating partially parallel acquisitions(grappa),” Magnetic Resonance in Medicine, vol. 47,no. 6, pp. 1202–1210, 2002.
  6. [6] P. Beatty et al., “Anti-aliased magnetic resonance im-age reconstruction using partially parallel encodeddata,” Oct. 21 2008, uS Patent 7,439,739.
  7. [7] J. Carlson, “Mri data acquisition and image re-construction from multiple, non-interacting receivercoils,” in Engineering in Medicine and Biology Soci-ety, 1989. Images of the Twenty-First Century., Pro-ceedings of the Annual International Conference ofthe IEEE Engineering in. IEEE, pp. 607–608.
  8. [8] M. Lustig and J. Pauly, “Spirit: Iterative self-consistent parallel imaging reconstruction from ar-bitrary k-space,” Magnetic Resonance in Medicine,vol. 64, no. 2, pp. 457–471, 2010.
  9. [9] M. Lustig, J. Santos, J. Lee, D. Donoho, and J. Pauly,“Application of compressed sensing for rapid mrimaging,” SPARS,(Rennes, France), 2005.
  10. [10] M. Lustig, D. Donoho, and J. Pauly, “Rapid mr imag-ing with compressed sensing and randomly under-sampled 3dft trajectories,” in Proc. 14th Ann. MeetingISMRM. Citeseer.
  11. [11] M. Lustig, J. Lee, D. Donoho, and J. Pauly, “Fasterimaging with randomly perturbed, under-sampledspirals and l1 reconstruction,” in Proceedings of the13th Annual Meeting of ISMRM, Miami Beach. Cite-seer, 2005, p. 685.
  12. [12] Z. Zhu, R. Yang, J. Zhang, and C. Zhang, “Com-pressed sensing mri by two-dimensional wavelet fil-ter banks,” in Multidimensional (nD) Systems (nDs),2011 7th International Workshop on. IEEE, 2011,pp. 1–6.
  13. [13] M. Murphy, M. Alley, J. Demmel, K. Keutzer,S. Vasanawala, and M. Lustig, “Fast ell 1-spirit com-pressed sensing parallel imaging mri: Scalable par-allel implementation and clinically feasible runtime,”Medical Imaging, IEEE Transactions on, no. 99, pp.1–1, 2012.
  14. [14] Y. Dong and J. Ji, “Novel compressive sensingmri methods with combined sparsifying transforms,”in Biomedical and Health Informatics (BHI), 2012IEEE-EMBS International Conference on. IEEE,2012, pp. 721–724.
  15. [15] M. Lustig, J. Santos, D. Donoho, and J. Pauly,“kt sparse: High frame rate dynamic mri exploitingspatio-temporal sparsity,” in Proceedings of the 13thAnnual Meeting of ISMRM, Seattle, 2006, p. 2420.
  16. [16] R. Bridson, “Fast poisson disk sampling in arbitrarydimensions,” in ACM SIGGRAPH. Citeseer, 2007,pp. 05–09.
  17. [17] S. Vasanawala, M. Murphy, M. Alley, P. Lai,K. Keutzer, J. Pauly, and M. Lustig, “Practical paral-lel imaging compressed sensing mri: Summary of twoyears of experience in accelerating body mri of pedi-atric patients,” in Biomedical Imaging: From Nanoto Macro, 2011 IEEE International Symposium on.IEEE, 2011, pp. 1039–1043.
  18. [18] C. Chang and J. Ji, “Compressed sensing mri withmulti-channel data using multi-core processors,” inEngineering in Medicine and Biology Society, 2009.EMBC 2009. Annual International Conference of theIEEE. IEEE, 2009, pp. 2684–2687.
  19. [19] M. Lusting, M. Alley, S. Vasanawala, D. Donoho, andJ. Pauly, “L1 spir-it: autocalibrating parallel imag-ing compressed sensing,” in Proc Intl Soc Mag ResonMed, vol. 17, p. 379.
  20. [20] E. Cand`es, “Compressive sampling,” in Proceed-ings of the International Congress of Mathematicians,vol. 3. Citeseer, 2006, pp. 1433–1452.
  21. [21] D. Donoho, “For most large underdetermined systemsof linear equations the minimal ??1-norm solution isalso the sparsest solution,” Communications on pureand applied mathematics, vol. 59, no. 6, pp. 797–829,2006.
  22. [22] E. Cand`es and M. Wakin, “An introduction to com-pressive sampling,” Signal Processing Magazine,IEEE, vol. 25, no. 2, pp. 21–30, 2008.
  23. [23] F. A.Razzaq, S. Mohamed, A. Bhatti, and S. Na-havandi, “Non-uniform sparsity in rapid compres-sive sensing mri,” in Systems Man and Cybernet-ics (SMC), 2012 IEEE International Conference on.IEEE, 2012, pp. 2253–2258.366
  24. [24] Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli,“Image quality assessment: From error visibility tostructural similarity,” Image Processing, IEEE Trans-actions on, vol. 13, no. 4, pp. 600–612, 2004.

Important Links:

Go Back