Deformation corrected compressed sensing (DC-CS): A novel framework for accelerated dynamic MRI

IEEE Transactions on Medical Imaging

Volumn 34, Issue 1, 2015, Pages 72-85

  Lingala, Sajan Goud ^a   Dibella, Edward ^b   Jacob, Mathews ^a  

^a University of Iowa   (United States)

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

Author keywords

Compressed sensing; deformation correction; dynamic MRI; Low rank regularization

Indexed keywords

COMPRESSED SENSING; DEFORMATION; MAGNETIC RESONANCE; MOTION ESTIMATION; OPTIMIZATION; QUADRATIC PROGRAMMING; SIGNAL RECONSTRUCTION; STRUCTURE (COMPOSITION);

COMPLEX OPTIMIZATION PROBLEMS; DEFORMABLE REGISTRATION; DEFORMATION CORRECTIONS; DYNAMIC MRI; LOW RANK REGULARIZATION; MYOCARDIAL PERFUSION MRI; QUADRATIC OPTIMIZATION; VARIABLE SPLITTING;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ARTICLE; BREATHING; CARDIAC GATED IMAGING; DEFORMATION CORRECTED COMPRESSED SENSING; FOURIER TRANSFORMATION; HEART LEFT VENTRICLE; HEART MUSCLE PERFUSION; HEART RIGHT VENTRICLE; HUMAN; HUMAN EXPERIMENT; IMAGE PROCESSING; IMAGE QUALITY; MYOCARDIAL PERFUSION IMAGING; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PERFUSION WEIGHTED IMAGING; RADIOLOGICAL PROCEDURES; PROCEDURES; RETROSPECTIVE STUDY; SIGNAL PROCESSING;

ALGORITHMS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PHANTOMS, IMAGING; RETROSPECTIVE STUDIES; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84920155292     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2014.2343953     Document Type: Article

References (67)

1. P. Kellman and A. E. Arai, "Imaging sequences for first pass perfusion- A review," J. Cardiovasc. Magn. Reson., vol. 9, no. 3, pp. 525-537, 2007.
2. M. A. Griswold, P. M. Jakob, R.M. Heidemann,M. Nittka, V. Jellus, J. Wang, B. Kiefer, and A. Haase, "Generalized autocalibrating partially parallel acquisitions (GRAPPA)," Magn. Reson. Med., vol. 47, no. 6, pp. 1202-1210, 2002.
3. S. Plein, A. Radjenovic, J. P.Ridgway,D.Barmby, J. P.Greenwood, S. G. Ball, and M. U. Sivananthan, "Coronary artery disease: Myocardial perfusion MR imaging with sensitivity encoding versus conventional angiography," Radiology, vol. 235, no. 2, pp. 423-430, 2005.
4. J. Tsao, P. Boesiger, and K. Pruessmann, "k-t BLAST and k-t SENSE: Dynamic MRI with high frame rate exploiting spatiotemporal correlations," Magn. Reson. Med., vol. 50, no. 5, pp. 1031-1042, 2003.
5. S. Plein, S. Ryf, J. Schwitter, A. Radjenovic, P. Boesiger, and S. Kozerke, "Dynamic contrast-enhanced myocardial perfusion MRI accelerated with k-t sense,"Magn. Reson. Med., vol. 58, no. 4, pp. 777-785, 2007.
6. B. Sharif, J. A. Derbyshire, A. Z. Faranesh, and Y. Bresler, "Patientadaptive reconstruction and acquisition in dynamic imaging with sensitivity encoding (PARADISE)," Magn. Reson. Med., vol. 64, no. 2, pp. 501-513, 2010.
7. E. DiBella, Y.Wu,A.Alexander,D.Parker,D. Green, andC.McGann, "Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies," Magn. Reson. Med., vol. 49, no. 5, pp. 895-902, 2003.
8. A. S. Gupta and Z. Liang, "Dynamic imaging by temporal modeling with principal component analysis," in Proc. 9th Ann. Meet. Int. Soc. Magn. Reson. Med, 2001, p. 10.
9. Z.-P. Liang, "Spatiotemporal imaging with partially separable functions," in Proc. 4th IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2007, pp. 988-991.
10. H. Pedersen, S. Kozerke, S. Ringgaard, K. Nehrke, andW. Kim, "k-t PCA: Temporally constrained k-t BLAST reconstruction using principal component analysis," Magn. Reson. Med., vol. 62, no. 3, pp. 706-716, 2009.
11. J. Tsao and S. Kozerke, "MRI temporal acceleration techniques," J. Magn. Reson. Imag., vol. 36, no. 3, pp. 543-560, 2012.
12. R. Otazo, D. Kim, L. Axel, and D. Sodickson, "Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI," Magn. Reson. Med., vol. 64, no. 3, pp. 767-776, 2010.
13. G. Adluru, S. Awate, T. Tasdizen, R. Whitaker, and E. DiBella, "Temporally constrained reconstruction of dynamic cardiac perfusion MRI," Magn. Reson. Med., vol. 57, no. 6, pp. 1027-1036, 2007.
14. S. G. Lingala, Y. Hu, E. DiBella, and M. Jacob, "Accelerated dynamic MRI exploiting sparsity and low-rank structure: kt SLR," IEEE Trans. Med. Imag., vol. 30, no. 5, pp. 1042-1054, May 2011.
15. J. P. Haldar and Z.-P. Liang, "Spatiotemporal imaging with partially separable functions: A matrix recovery approach," in Proc. IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2010, pp. 716-719.
16. J. Trzasko, A. Manduca, and E. Borisch, "Local versus global low-rank promotion in dynamic MRI series reconstruction," in Proc. Int. Symp. Magn. Reson. Med, 2011, p. 4371.
17. S. G. Lingala, M. Nadar, C. Chefd'Hotel, L. Zhang, and M. Jacob, "Unified reconstruction and motion estimation in cardiac perfusion MRI," in Proc. IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2011, pp. 65-68.
18. J. Fessler, "Optimization transfer approach to joint registration/reconstruction for motion-compensated image reconstruction," in Proc. IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2010, pp. 596-599.
19. F. Odille, P.-A. Vuissoz, P.-Y. Marie, and J. Felblinger, "Generalized reconstruction by inversion of coupled systems (GRICS) applied to free-breathing MRI," Magn. Reson. Med., vol. 60, no. 1, pp. 146-157, 2008.
20. M. Jacobson and J. A. Fessler, "Joint estimation of image and deformation parameters in motion-corrected PET," in IEEE Nucl. Sci. Symp. Conf. Rec., 2003, vol. 5, pp. 3290-3294.
21. M. Reyes, G. Malandain, P. M. Koulibaly, M. Gonzalez-Ballester, and J. Darcourt, "Model-based respiratory motion compensation for emission tomography image reconstruction," Phys. Med. Biol., vol. 52, no. 12, p. 3579, 2007.
22. H. Jung and J. C. Ye, "Motion estimated and compensated compressed sensing dynamicmagnetic resonance imaging:What we can learn from video compression techniques," Int. J. Imag. Syst. Technol., vol. 20, no. 2, pp. 81-98, 2010.
23. M. S. Asif, L. Hamilton, M. Brummer, and J. Romberg, "Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI," Magn. Reson. Med., vol. 70, no. 3, pp. 800-812, Sep. 2013.
24. P. Kellman, C. Chefd'hotel, C. H. Lorenz, C. Mancini, A. E. Arai, and E. R.McVeigh, "High spatial and temporal resolution cardiac cineMRI from retrospective reconstruction of data acquired in real time using motion correction and resorting," Magn. Reson. Med., vol. 62, no. 6, pp. 1557-1564, 2009.
25. P. Kellman, C. Chefd'hotel, C. H. Lorenz, C. Mancini, A. E. Arai, and E. R. McVeigh, "Fully automatic, retrospective enhancement of realtime acquired cardiac cine MR images using image-based navigators and respiratory motion-corrected averaging," Magn. Reson. Med., vol. 59, no. 4, pp. 771-778, 2008.
26. M. Usman, D. Atkinson, F. Odille, C. Kolbitsch, G. Vaillant, T. Schaeffter, P. G. Batchelor, and C. Prieto, "Motion corrected compressed sensing for free-breathing dynamic cardiac MRI,"Magn. Reson. Med., vol. 70, pp. 504-516, 2013.
27. M. S. Hansen, T. S. Sørensen, A. E. Arai, and P. Kellman, "Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction," Magn. Reson. Med., vol. 68, no. 3, pp. 741-750, 2012.
28. M. J. Ledesma-Carbayo, P. Kellman, A. E. Arai, and E. R. McVeigh, "Motion corrected free-breathing delayed-enhancement imaging of myocardial infarction using nonrigid registration," J. Magn. Reson. Imag., vol. 26, no. 1, pp. 184-190, 2007.
29. G. Wollny, M. J. Ledesma-Carbayo, P. Kellman, and A. Santos, "A new similarity measure for non-rigid breathing motion compensation of myocardial perfusion MRI," in Proc. 30th Annu. Int. Conf.e IEEE Eng. Med. Biol. Soc., 2008, pp. 3389-3392.
30. G. Wollny, P. Kellman, A. Santos, and M. J. Ledesma-Carbayo, "Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis,"Med. Image Anal., vol. 16, no. 5, pp. 1015-1028, 2012.
31. M. B. Stegmann, H. Olafsdóttir, and H. B. Larsson, "Unsupervisedmotion- compensation of multi-slice cardiac perfusion MRI," Med. Image Anal., vol. 9, no. 4, pp. 394-410, 2005.
32. G. Adluru, E. V. DiBella, and M. C. Schabel, "Model-based registration for dynamic cardiac perfusion MRI," J. Magn. Reson. Imag., vol. 24, no. 5, pp. 1062-1070, 2006.
33. G. Wollny, P. Kellman, A. Santos, and M.-J. Ledesma, "Nonrigid motion compensation of free breathing acquired myocardial perfusion data," in Bildverarbeitung für die Medizin, 2011, pp. 84-88.
34. F. Khalifa, G. M. Beache, A. Firjani, K. Welch, G. Gimel'farb, and A. El-Baz, "A new nonrigid registration approach formotion correction of cardiac first-pass perfusion MRI," in Proc. 19th IEEE Int. Conf. Image Process., 2012, pp. 1665-1668.
35. H. Pedersen, H. Ólafsdóttir, R. Larsen, and H. B. Larsson, "A unifying model of perfusion and motion applied to reconstruction of sparsely sampled free-breathing myocardial perfusionMRI," in Proc. IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2010, pp. 752-755.
36. R. Otazo, D. Kim, L. Axel, and D. Sodickson, "Combination of compressed sensing and parallel imaging with respiratory motion correction for highly-accelerated cardiac perfusion MRI," J. Cardiovasc. Magn. Reson., vol. 13, p. O98, 2011.
37. X. Chen, M. Salerno, Y. Yang, and F. H. Epstein, "Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: Block low-rank sparsity with motion-guidance (BLOSM)," Magn. Reson. Med., vol. 72, no. 4, pp. 1028-1038, 2014.
38. H. Yoon, K. Kim, D. Kim, Y. Bresler, and J. Ye, "Motion adaptive patch-based low-rank approach for compressed sensing cardiac cine MRI," IEEE Trans. Med. Imag., 2014, to be published.
39. G. Adluru and E. V. DiBella, "Reconstruction with diffeomorphic motion compensation for undersampled dynamicMRI," in SPIE Opt. Eng. Appl. Int. Soc. Opt. Photon., 2013, pp. 88 581X-88 581X.
40. Demons deformable image registration Sep. 2008 [Online]. Available: http://www.mathworks.com/matlabcentral/fileexchange/21451-multimodality
41. J. Kybic and M. Unser, "Fast parametric elastic image registration," IEEE Trans. Image Process., vol. 12, no. 11, pp. 1427-1442, Nov. 2003.
42. S. Y. Chun and J. A. Fessler, "A simple regularizer for B-spline nonrigid image registration that encourages local invertibility," IEEE J. Sel. Topics Signal Process., vol. 3, no. 1, pp. 159-169, Feb. 2009.
43. C. Chefd'Hotel, G. Hermosillo, and O. Faugeras, "Flows of diffeomorphisms for multimodal image registration," in Proc. IEEE Int. Symp. Biomed. Imag., 2002, pp. 753-756.
44. M. Afonso, J. Bioucas-Dias, and M. Figueiredo, "Fast image recovery using variable splitting and constrained optimization," IEEE Trans. Image Process., vol. 19, no. 9, pp. 2345-2356, Sep. 2010.
45. S. Ramani and J. A. Fessler, "A splitting-based iterative algorithm for accelerated statistical X-ray CT reconstruction," IEEE Trans. Med. Imag., vol. 31, no. 3, pp. 677-688, Mar. 2012.
46. R. T. Rockafellar, Convex Analysis. Princeton, NJ: Princeton Univ. Press, 1997.
47. D. L. Donoho, "De-noising by soft-thresholding," IEEE Trans. Inf. Theory, vol. 41, no. 3, pp. 613-627, May 1995.
48. J.-F. Cai, E. J. Candés, and Z. Shen, "A singular value thresholding algorithm for matrix completion," SIAM J. Optimizat., vol. 20, no. 4, pp. 1956-1982, 2010.
49. J. Yang, Y. Zhang, and W. Yin, "A fast alternating direction method for TVL1-L2 signal reconstruction from partial Fourier data," IEEE J. Sel. Topics Signal Process., vol. 4, no. 2, pp. 288-297, Apr. 2010.
50. J.-P. Thirion, "Image matching as a diffusion process: An analogy with Maxwell's demons," Med. Image Anal., vol. 2, no. 3, pp. 243-260, 1998.
51. H. Wang, L. Dong, J. O'Daniel, R. Mohan, A. S. Garden, K. K. Ang, D. A. Kuban, M. Bonnen, J. Y. Chang, and R. Cheung, "Validation of an accelerated ?demons' algorithm for deformable image registration in radiation therapy," Phys. Med. Biol., vol. 50, no. 12, p. 2887, 2005.
52. X. Pennec, P. Cachier, and N. Ayache, "Understanding the "demon's algorithm": 3D non-rigid registration by gradient descent," in Medical Image Computing and Computer-Assisted Intervention-MICCAI'99. New York: Springer, 1999, pp. 597-605.
53. M. Bro-Nielsen, Medical image registration and surgery simulation IMM-PHD-1996-25 1997.
54. Y. Hu, S. Lingala, and M. Jacob, "A fast majorize-minimize algorithm for the recovery of sparse and low-rank matrices," IEEE Trans. Image Process., vol. 21, no. 2, pp. 742-753, Feb. 2012.
55. J. Yang and Y. Zhang, "Alternating direction algorithms for-problems in compressive sensing," SIAM J. Sci. Comput., vol. 33, no. 1, pp. 250-278, 2011.
56. J. Kybic, P. Thévenaz, and M. Unser, "Multiresolution spline warping for EPI registration," in Proc. SPIE: Math. Imag.-Wavelet Appl. Signal Image Process., Denver, CO, 1999, pp. 571-579.
57. B. Sharif and Y. Bresler, "Physiologically improved NCAT phantom (PINCAT) enables in-silico study of the effects of beat-to-beat variability on cardiac MR," in Proc. Annu. Meet. ISMRM, 2007, p. 3418.
58. E. DiBella, J. Fluckiger, L. Chen, T. Kim, N. Pack, B. Matthews, G. Adluru, T. Priester, S. Kuppahally, and R. Jiji et al., "The effect of obesity on regadenoson-inducedmyocardial hyperemia: A quantitative magnetic resonance imaging study," in Int. J. Cardiovasc. Imag., 2011, pp. 1-10.
59. M. Buehrer, K. Pruessmann, P. Boesiger, and S. Kozerke, "Array compression for MRI with large coil arrays," Magn. Reson. Med., vol. 57, no. 6, pp. 1131-1139, 2007.
60. C. Bilen, I. Selesnick, Y. Wang, R. Otazo, D. Kim, L. Axel, and D. Sodickson, "On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., 2010, pp. 630-633.
61. S. Ravishankar and Y. Bresler, "MR image reconstruction from highly undersampled k-space data by dictionary learning," IEEE Trans. Med. Imag., vol. 30, no. 5, pp. 1028-1041, May 2011.
62. S.G.Lingala andM. Jacob, "Blind compressive sensing dynamicMRI," IEEE Trans. Med. Imag., vol. 32, no. 6, pp. 1132-1145, Jun. 2013.
63. S. Lingala, Y. Hu, E. Di Bella, and M. Jacob, "Accelerated dynamic MRI exploiting sparsity and low-rank structure: kt SLR," IEEE Trans. Med. Imag., vol. 30, no. 5, pp. 1042-1054, May 2011.
64. J. P. Haldar and D. Hernando, "Rank-constrained solutions to linear matrix equations using powerfactorization," IEEE Signal Process. Lett., vol. 16, no. 7, pp. 584-587, Jul. 2009.
65. S. G. Lingala, E. DiBella, G. Adluru, C. McGann, and M. Jacob, "Accelerating free breathing myocardial perfusion MRI using multi coil radial k-t SLR," Phys. Med. Biol., vol. 58, no. 20, p. 7309, 2013.
66. B. Zhao, J. P. Haldar, A. G. Christodoulou, and Z.-P. Liang, "Image reconstruction from highly undersampled-space data with joint partial separability and sparsity constraints," IEEE Trans.Med. Imag., vol. 31, no. 9, pp. 1809-1820, Sep. 2012.
67. S. Y. Chun, C. Schretter, and J. A. Fessler, "Sufficient condition for local invertibility of spatio-temporal 4d b-spline deformations," in Proc. IEEE Int. Symp. Biomed. Imag., From Nano to Macro, 2010, pp. 1221-1224.