K-T ISD: Compressed sensing with iterative support detection for dynamic MRI

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2011, Pages 1264-1267

  Liang, Dong ^a   Dibella, Edward V R ^b   Chen, Rong Rong ^c   Ying, Leslie ^a  

^a University of Wisconsin Milwaukee   (United States)

^b UNIVERSITY OF UTAH SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF UTAH   (United States)

Author keywords

Compressed sensing; dynamic MRI; k t Iterative Support Detection (k t ISD); partially known support; truncated 1 minimization

Indexed keywords

COMPRESSED SENSING; DYNAMIC MRI; K-T ITERATIVE SUPPORT DETECTION (K-T ISD); PARTIALLY KNOWN SUPPORT; TRUNCATED 1 MINIMIZATION;

IMAGE RECONSTRUCTION; MEDICAL IMAGING;

MAGNETIC RESONANCE IMAGING;

EID: 80055047240     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2011.5872631     Document Type: Conference Paper

References (12)

1. E. J. Candès, J. Romberg and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Information Theory, vol. 52, pp. 489-509, 2006.
2. D. Donoho, "Compressed sensing," IEEE Trans. on Information Theory, vol. 52, pp. 1289 - 1306, 2006.
3. H. Jung, J. C. Ye, and E.Y. Kim, "Improved k-t BLAST and k-t SENSE using FOCUSS," Phys. Med. Biol., vol. 52, no. 11, pp. 3201-3226, 2007.
4. H. Jung, K. Sung, K.S. Nayak, E.Y. Kim, and J.C. Ye, "k-t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI," Magn. Reson. Med., vol. 61, no. 1, pp. 103-116, 2009.
5. U. Gamper, P. Boesiger, and S. Kozerke, "Compressed sensing in dynamic MRI," Magn. Reson. Med., vol. 59, no. 2, pp. 365-373, 2008.
6. M. Lustig, J. M. Santos, D. L. Donoho, and J. M. Pauly, "k-t SPARSE: high frame rate dynamic MRI exploiting spatio-temporal sparsity," in Proc. Int. Soc. Mag. Reson. Med., Seattle, WA, 2006, p. 2420.
7. C. J. Miosso, R. von Borries, M. Argàez, L. Velazquez, C. Quintero, and C. M. Potes, "Compressive sensing reconstruction with prior information by iteratively reweighted least-squares," IEEE Trans. Signal Process., vol. 57, no. 6, pp. 2424-2431, 2009.
8. L. Jacques, "A short note on compressed sensing with partially known signal support," Signal Process., vol. 90, no. 12, pp. 3308-331, 2010.
9. Y. Wang and W. Yin, "Sparse signal reconstruction via iterative support detection," SIAM J. Imag. Sci., vol. 3, no. 3, pp. 462-491, 2010.
10. N. Vaswani, and W. Lu, "Modified-CS: modifying compressive sensing for problems with partially known support," IEEE Trans. Signal Process., vol. 58, no. 9, pp. 4595-4607, 2010.
11. N. Aggarwal, and Y. Bresler, "Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI," Inverse Problems, vol. 24, no. 4, pp. 045015-1 - 045015-29, 2008.
12. C. Brinegar, H. Zhang, Y.-J. L. Wu, L. M. Foley, T. K. Hitchens, Q. Ye, D. Pocci, F. Lam, C. Ho, and Z.-P. Liang, "Realtime cardiac MRI using prior spatial-spectral information," in Proc. 31st Annu. Int. Conf. IEEE EMBS, Minneapolis, MN, 2009, pp. 4383-4386.