Enhancement of four-dimensional cone-beam computed tomography by compressed sensing with Bregman iteration

Journal of X-Ray Science and Technology

Volumn 21, Issue 2, 2013, Pages 177-192

  Choi, Kihwan ^a,b   Fahimian, Benjamin P ^a   Li, Tianfang ^c   Suh, Tae Suk ^d   Lei, Xing ^a,d  

^a STANFORD UNIVERSITY   (United States)

^b Stanford University   (United States)

^c UNIVERSITY OF PITTSBURGH MEDICAL CENTER   (United States)

^d The Catholic University of Korea   (South Korea)

Author keywords

Bregman iteration; compressed sensing; fast first order method; Four dimensional cone beam computed tomography

Indexed keywords

BREGMAN ITERATION; CONE-BEAM COMPUTED TOMOGRAPHY; FILTERED BACK-PROJECTION; FIRST-ORDER METHODS; FOUR-DIMENSIONAL CONE-BEAM COMPUTED TOMOGRAPHIES; GRADIENT-BASED METHOD; UNCONSTRAINED OPTIMIZATION PROBLEMS; UNCONSTRAINED PROBLEMS;

COMPRESSED SENSING; COMPUTERIZED TOMOGRAPHY; IMAGE RECONSTRUCTION; SENSORS;

ITERATIVE METHODS;

ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; CONE BEAM COMPUTED TOMOGRAPHY; FOUR DIMENSIONAL COMPUTED TOMOGRAPHY; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; PROCEDURES; RADIOGRAPHY; TRUNK; ARTICLE; METHODOLOGY;

ALGORITHMS; COMPUTER SIMULATION; CONE-BEAM COMPUTED TOMOGRAPHY; FOUR-DIMENSIONAL COMPUTED TOMOGRAPHY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; PHANTOMS, IMAGING; TORSO;

EID: 84880236247     PISSN: 08953996     EISSN: None     Source Type: Journal    
DOI: 10.3233/XST-130371     Document Type: Article

References (37)

1. A.J. David, H.S. Jeffrey, W.W. John and A.M. Alvaro, Flat-panel cone-beam computed tomography for image-guided radiation therapy, Int J Radiat Oncol, Biol, Phys 53(5) (2002), 1337-1349
2. Y. Yang, E. Schreibmann, T. Li, C. Wang and L. Xing, Evaluation of on-board kV cone beam CT (CBCT)-based dose calculation, Phys Med Biol 52(3) (2007), 685-705
3. L. Lee, Q.T. Le and L. Xing, Retrospective IMRT dose reconstruction based on cone-beam CT and MLC log-file, Int J Radiat Oncol, Biol, Phys 70(2) (2008), 634-644
4. R.D. Timmerman and L. Xing, Image guided and adaptive radiation therapy, Lippincott Williams & Wilkins, Baltimore, 2009
5. L. Xing, B. Thorndyke, E. Schreibmann, Y. Yang, T-F. Li, G-Y. Kim, G. Luxton and A. Koong, Overview of imageguided radiation therapy, Med Dosim 31(2) (2006), 91-112
6. J.J. Sonke, L. Zijp, P. Remeijer and M. van Herk, Respiratory correlated cone beam CT, Med Phys 32 (2005), 1176
7. T. Li, E. Schreibmann, B. Thorndyke, G. Tillman, A. Boyer, A. Koong, K. Goodman and L. Xing, Radiation dose reduction in four-dimensional computed tomography, Med Phys 32 (2005), 3650-3660
8. T. Li, A. Koong and L. Xing, Enhanced 4D cone-beam CT with inter-phase motion model, Med Phys 34(9) (2007), 3688-3695
9. C.J. Ritchie, J. Hsieh, M.F. Gard, J.D. Godwin, Y. Kim and C.R. Crawford, Predictive respiratory gating: A new method to reduce motion artifacts on CT scans, Radiology 190 (1994), 847-852
10. T. Li, L. Xing, P. Munro, C. McGuinness, M. Chao, Y. Yang, B. Loo and A. Koong, Four-dimensional cone-beam computed tomography using an on-board imager, Med Phys 33 (2006), 3825-3833
11. J. Zou, J. Gui, J. Rong, Z. Hu, Q. Zhang and D. Xia, Investigation of BPF algorithm in cone-beam CT with 2D general trajectories, J X-Ray Sci Technol 20(3) (2012), 351-362
12. L. Li, Y. Xing, Z. Chen, L. Zhang and K. Kang, A curve-filtered FDK (C-FDK) reconstruction algorithm for circular cone-beam CT, J X-Ray Sci Technol 19(3) (2011), 355-371
13. L. Zeng and X. Zou, Katsevich-type reconstruction for dual helical cone-beam CT, J X-Ray Sci Technol 18(4) (2010), 353-367
14. C. Ji, Accurate 3D data stitching in circular cone-beam micro-CT, J X-Ray Sci Technol 18(2) (2010), 99-110
15. G-H. Chen, J. Tang and S. Leng, Prior image constrained compressed sensing (PICCS): A method to accuratedly reconstruct dynamic CT images from highly undersampled projection data sets, Med Phys 35 (2008), 660-663
16. E.Y. Sidky and X. Pan, Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization, Phys Med Biol 53(17) (2008), 4777-4807
17. S. Osher, M. Burger, D. Goldfarb, J. Xu and W. Yin, An iterative regularization method for total variation-based image restoration, Multiscale Model Simul 4(2) (2005), 460-489
18. W. Yin, S. Osher, D. Goldfarb and J. Darbon, Bregman iterative algorithm 1-minimization with applications to compressed sensing, SIAM J Imag Sci 1(1) (2008), 143-168
19. L.M. Bergman, The relaxation method of finding the common points of convex sets and its application to the solution of problems in convex optimization, USSR Computational Mathematics and Mathematical Physics 7(3) (1967), 200-217
20. A.C. Kak and M. Slaney, Principles of computerized tomographic imaging, IEEE Service Center, Piscataway, NJ, 1988
21. J.Wang, T. Li and L. Xing, Iterative image reconstruction for CBCT using edge-preserving prior, Med Phys 36(1) (2009), 252-260
22. L. Zhu, J. Wang and L. Xing Noise suppression in scatter correction for cone-beam CT, Med Phys 36 (2009), 741-752
23. T.F. Li, X. Li, J. Wang, J.H. Wen, H.B. Lu, J. Hsieh and Z.R. Liang Nonlinear sinogram smoothing for low-dose x-ray CT, IEEE Trans Nucl Sci 51 (2004), 2505-2513
24. Y. Long, J.A. Fessler and J.M. Balter, 3D forward and back-projection for X-ray CT using separable footprints, IEEE Trans Med Imaging 29(11) (2010), 1839-1850
25. E.J. Candès, J. Romberg and T. Tao, Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information, IEEE Trans Inf Theory 52(2) (2006), 489-509
26. E.J. Candès and T. Tao, Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans Inf Theory 52(12) (2006), 5406-5425
27. D. Donoho, Compressed sensing, IEEE Trans Info Theory 52(4) (2006), 1289-1306
28. K. Choi, J.Wang, L. Zhu, T-S. Suh, S. Boyd and L. Xing, Compressed sensing based cone-beam computed tomography reconstruction with a first-order method, Med Phys 37 (2010), 5113-5125
29. J. Song, Q.H. Liu, G.A. Johnson and C.T. Badea, Sparseness prior based iterative image reconstruction for retrospectively gated cardiac micro-CT, Med Phys 34(11) (2007), 4476-4483
30. A. Beck and M. Teboulle, A fast iterative shrinkage-thresholding algorithm for linear inverse problems, SIAM J Imag Sci 2(1) (2009), 183-202
31. P. Getreuer, Rudin-osher-fatemi total variation denoising using split bregman, Image Processing On Line (2012).
32. S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004
33. R.T. Rockafellar, Convex Analysis, Princeton Univ Pr, 1997
34. S. Becker, J. Bobin and E.J. Candnès, NESTA: A fast and accurate first-order method for sparse recovery, SIAM J Imag Sci 4(1) (2011), 1-39
35. J.F. Cai, S. Osher and Z. Shen, Convergence of the linearized Bregman iteration for -1-norm minimization, Math Comp 78(268) (2009), 2127-2136
36. X. Pan, E.Y. Sidky and M. Vannier, Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction? Inv Prob 25 (2009), 123009
37. X. Jia, Y. Lou, J. Lewis, R. Li, X. Gu, C. Men, W. Song and S. Jiang, GPU-based fast low-dose cone beam CT reconstruction via total variation, J X-Ray Sci Technol 19(2) (2011), 139-154