Accelerating advanced MRI reconstructions on GPUs

Journal of Parallel and Distributed Computing

Volumn 68, Issue 10, 2008, Pages 1307-1318

  Stone, S S ^a   Haldar, J P ^b   Tsao, S C ^a   Hwu, W m W ^a   Sutton, B P ^a   Liang, Z P ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b University of Illinois at Urbana Champaign   (United States)

Author keywords

CUDA; GPU computing; MRI; Reconstruction

Indexed keywords

MAGNETIC RESONANCE IMAGING; RESONANCE;

CUDA; GPU COMPUTING; MRI; RECONSTRUCTION;

THREE DIMENSIONAL;

EID: 51449100575     PISSN: 07437315     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jpdc.2008.05.013     Document Type: Article

References (43)

1. AMD stream processor. http://ati.amd.com/products/streamprocessor/index.html
2. M.M. Baskaran, U. Bondhugula, J. Ramanujam, A. Rountev, P. Sadayappan, A compiler framework for optimization of affine loop nests for general purpose computations on gpus, Technical Report OSU-CISRC-12/07-TR78, Ohio State University, Dec. 2007
3. Bernstein M.A., King K.F., and Zhou X.J. Handbook of MRI Pulse Sequences (2004), Elsevier Academic Press, Burlington, MA
4. Bockenbach O., Knaup M., and Kachelrieß M. Implementation of a cone-beam backprojection algorithm on the Cell Broadband Engine processor. SPIE Medical Imaging 2007: Physics of Medical Imaging (2007)
5. I. Buck, Brook specification v0.2, October 2003
6. B. Cabral, N. Cam, J. Foran, Accelerated volume rendering and tomographic reconstruction using texture mapping hardware, in: 1994 Symposium on Volume Visualization, 1994
7. Cg. http://developer.nvidia.com/page/cg_main.html
8. K. Chidlow, T. Möller, Rapid emission tomography reconstruction, in: Int'l Workshop on Volume Graphics, 2003
9. Concus P., Golub G., and O'Leary D. A Generalized Conjugate Gradient Method for the Numerical Solution of Elliptic Partial Differential Equations (1976), Academic Press, New York
10. DirectX developer center. http://www.msdn.com/directx/
11. J. Dongarra, Compressed Row Storage CRS. http://netlib.org/utk/papers/templates/node91.html
12. Fessler J.A., Lee S., Olafsson V.T., Shi H.R., and Noll D.C. Toeplitz-based iterative image reconstruction for MRI with correction for magnetic field inhomogeneity. IEEE Transactions on Signal Processing 53 9 (2005) 3393-3402
13. Glover G. Simple analytic spiral k-space algorithm. Magnetic Resonance in Medicine 42 2 (1999) 412-415
14. Haldar J., Hernando D., Song S.-K., and Liang Z. Anatomically constrained reconstruction from noisy data. Magnetic Resonance in Medicine 59 (2008) 810-818
15. J.P. Haldar, Z. Liang, Joint reconstruction of noisy high-resolution MR image sequences, in: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008, pp. 752-755
16. Hansen M., Atkinson D., and Sørensen T. Cartesian SENSE and k-t SENSE reconstruction using commodity graphics hardware. Magnetic Resonance in Medicine 59 3 (2008) 463-468
17. Hestenes M., and Stiefel E. Methods of conjugate gradients for solving linear systems. Journal of Research of the National Bureau of Standards 49 6 (1952) 409-436
18. Jackson J.I., Meyer C.H., Nishimura D.G., and Macovski A. Selection of a convolution function for Fourier inversion using gridding. IEEE Transactions on Medical Imaging 10 3 (1991) 473-478
19. T. Jansen, B. von Rymon-Lipinski, N. Hanssen, E. Keeve, Fourier volume rendering on the GPU using a split-stream FFT, in: 9th International Fall Workshop on Vision, Modeling, and Visualization, 2004
20. Koay C., Sarlls J., and Ozarslan E. Three dimensional analytical magnetic resonance imaging phantom in the Fourier domain. Magnetic Resonance in Medicine 58 (2007) 430-436
21. Meijerink J., and van der Vorst H. An iterative solution method for linear systems of which the coefficient matrix is a symmetric M-matrix. Mathematics of Computation 31 137 (1977) 148-162
22. Mueller K., Xu F., and Neophytou N. Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?. SPIE Electronic Imaging 2007, Computational Imaging V Keynote (2007)
23. Mueller K., and Yagel R. Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware. IEEE Transactions on Medical Imaging 19 12 (2000) 1227-1237
24. J. Nickolls, I. Buck, NVIDIA CUDA software and GPU parallel computing architecture, Microprocessor Forum, May 2007
25. NVIDIA corporation. CUDA CUFFT Library, version 1.1, 2007
26. NVIDIA corporation. NVIDIA CUDA Programming Guide, version 1.1, 2007
27. Owens J., Luebke D., Govindaraju N., Harris M., Krger J., Lefohn A., and Purcell T. A survey of general-purpose computation on graphics hardware. Computer Graphics Forum 26 1 (2007) 80-113
28. Pruessmann K.P., Weiger M., Börnert P., and Boesiger P. Advances in sensitivity encoding with arbitrary k-space trajectories. Magn. Res. Med. 46 4 (2001) 638-651
29. S. Ryoo, C. Rodrigues, S. Baghsorkhi, S. Stone, D. Kirk, W. Hwu, Optimization principles and application performance evaluation of a multithreaded GPU using CUDA, in: Symposium on Principles and Practice of Parallel Programming, PPOPP, 2008
30. S. Ryoo, C. Rodrigues, S. Stone, S. Baghsorkhi, S. Ueng, J. Stratton, W. Hwu, Optimization space pruning for a multithreaded GPU, in: International Symposium on Code Generation and Optimization, CGO, 2008
31. M. Sakamoto, M. Murase, Parallel implementation for 3-D CT image reconstruction on Cell Broadband Engine, in: International Conference on Multimedia and Expo, 2007
32. T. Schiwietz, T. Chang, P. Speier, R. Westermann, MR image reconstruction using the GPU, in: SPIE Medical Imaging 2006, 2006
33. Schomberg H., and Timmer J. The gridding method for image reconstruction by Fourier transformation. IEEE Transactions on Medical Imaging 14 3 (1995) 596-607
34. M. Segal, K. Akeley, The OpenGL Graphics System: A Specification (Version 2.0). Silicon Graphics, Inc., October 2004
35. Sørensen T., Schaeffter T., Noe K., and Hansen M. Accelerating the non-equispaced fast Fourier transform on commodity graphics hardware. IEEE Transactions on Medical Imaging 27 4 (2008) 538-547
36. S. Stone, J. Haldar, S. Tsao, W. Hwu, B. Sutton, Z. Liang, Accelerating advanced MRI reconstructions on GPUs, in: Proceedings of International Conference on Computing Frontiers CF, 2008
37. S. Stone, H. Yi, J. Haldar, W. Hwu, B. Sutton, Z. Liang, How GPUs can improve the quality of magnetic resonance imaging, in: First Workshop on General Purpose Processing on Graphics Processing Units, GPGPU, 2007
38. Sumanaweera T., and Liu D. Medical image reconstruction with the FFT. In: Pharr M. (Ed). GPU Gems 2: Programming Techniques for High-Performance Graphics and General-Purpose Computation (2005), Addison-Wesley 765-784
39. Sutton B.P., Noll D.C., and Fessler J.A. Fast, iterative image reconstruction for MRI in the presence of field inhomogeneities. IEEE Transactions on Medical Imaging 22 2 (2003) 178-188
40. D. Tarditi, S. Puri, J. Oglesby, Accelerator: Using data parallelism to program GPUs for general-purpose uses, in: Int'l Conference on Architectural Support for Programming Languagues and Operating Systems, ASPLOS-XII, 2006
41. P. Trancoso, M. Charalambous, Exploring graphics processor performance for general purpose applications, in: Euromicro Symposium on Digital System Design, Architectures, Methods, and Tools, DSD 2005, 2005
42. F.T.A.W. Wajer, Non-Cartesian MRI scan time reduction through sparse sampling, PhD thesis, Technische Universiteit Delft, Delft, Netherlands, 2001
43. X. Xue, A. Cheryauka, D. Tubbs, Acceleration of fluoro-CT reconstruction for a mobile C-Arm on GPU and FPGA hardware: A simulation study, in: SPIE Medical Imaging 2006, 2006