Statistical image reconstruction for low-dose CT using nonlocal means-based regularization

Computerized Medical Imaging and Graphics

Volumn 38, Issue 6, 2014, Pages 423-435

  Zhang, Hao ^a,b   Ma, Jianhua ^a,c   Wang, Jing ^d   Liu, Yan ^a   Lu, Hongbing ^e   Liang, Zhengrong ^a,b  

^a STONY BROOK UNIVERSITY   (United States)

^b STONY BROOK UNIVERSITY   (United States)

^c SOUTHERN MEDICAL UNIVERSITY   (China)

^d UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^e FOURTH MILITARY MEDICAL UNIVERSITY   (China)

Author keywords

Low dose CT; Nonlocal means; Regularization; Statistical image reconstruction

Indexed keywords

IMAGE RECONSTRUCTION; MARKOV PROCESSES; NOISE ABATEMENT;

FILTERED BACK-PROJECTION METHODS; IMAGE NOISE REDUCTION; IMAGE PROCESSING APPLICATIONS; LOW-DOSE CT; MARKOV RANDOM FIELD MODELS; NON-LOCAL MEANS; REGULARIZATION; STATISTICAL IMAGE RECONSTRUCTION;

COMPUTERIZED TOMOGRAPHY;

ARTICLE; BACK PROPAGATION; COMPUTER ASSISTED TOMOGRAPHY; FILTERED BACK PROJECTION; HIDDEN MARKOV MODEL; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; IMAGE RECONSTRUCTION; IMAGING PHANTOM; NOISE REDUCTION; NORMAL DISTRIBUTION; PRIORITY JOURNAL; RADIATION DOSE; RADIATION EXPOSURE; RADIOLOGY PHANTOM; STATISTICAL IMAGE RECONSTRUCTION; ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; PROBABILITY; PROCEDURES; STATISTICS;

ALGORITHMS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MARKOV CHAINS; RADIATION DOSAGE; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; STATISTICS AS TOPIC; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84906064806     PISSN: 08956111     EISSN: 18790771     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2014.05.002     Document Type: Article

References (62)

1. Brenner D., Hall E. Computed tomography - an increasing source of radiation exposure. N Engl J Med 2007, 357:2277-2284.
2. Wang J., Lu H., Liang Z., Xing L. Recent development of low-dose cone-beam computed tomography. Curr Med Imaging Rev 2010, 6:72-81.
3. Beister M., Kolditz D., Kalender W. Iterative reconstruction methods in X-ray CT. Phys Med 2012, 28:94-108.
4. Sauer K., Bouman C. A local update strategy for iterative reconstruction from projections. IEEE Trans Signal Process 1993, 41:534-548.
5. Bouman C., Sauer K. A unified approach to statistical tomography using coordinate descent optimization. IEEE Trans Image Process 1996, 5:480-492.
6. Fessler J.A. Statistical imaging reconstruction methods. Handbook of medical imaging 2000, Bellingham, Washington. M. Sonka, J.M. Fitzpatrick (Eds.).
7. Elbakri A., Fessler J.A. Statistical image reconstruction for polyenergetic X-ray computed tomography. IEEE Trans Med Imaging 2002, 21(2):89-99.
8. Li T., Li X., Wang J., Wen J., Lu H., Hsieh J., Liang Z. Nonlinear sinogram smoothing for low-dose X-ray CT. IEEE Trans Nucl Sci 2004, 51:2505-2513.
9. Wang J., Li T., Lu H., Liang Z. Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography. IEEE Trans Med Imaging 2006, 25:1272-1283.
10. Thibault J.B., Sauer K., Bouman C., Hsieh J. A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 2007, 34:4526-4544.
11. Wang J., Li T., Xing L. Iterative image reconstruction for CBCT using edge-preserving prior. Med Phys 2009, 36:252-260.
12. Tang J., Nett B., Chen G. Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms. Phys Med Biol 2009, 54:5781-5804.
13. Ouyang L., Solberg T., Wang J. Effects of the penalty on the penalized weighted least-squares image reconstruction for low-dose CBCT. Phys Med Biol 2011, 56:5535-5552.
14. Xu Q., Yu H., Mou X., Zheng L., Hsieh J., Wang G. Low-dose X-ray CT reconstruction via dictionary learning. IEEE Trans Med Imaging 2012, 31:1682-1697.
15. Theriault-Lauzier P., Chen G. Characterization of statistical prior image constrained compressed sensing II: application to dose reduction. Med Phys 2013, 40(2):021902.
16. Barrett H.H., Myers J.K. Foundations of image science 2003, Wiley-Interscience, New York. 1 edition (October 24).
17. Manduca A., Yu L., Trzasko J.D., Khaylova N., Kofler J.M., McCollough C.H., Fletcher J.G. Projection space denosing with bilateral filtering and CT noise modeling for dose reduction in CT. Med Phys 2009, 36:4911-4919.
18. Hsieh J. Computed tomography principle, design, artifacts and recent advances 2003, Bellingham, Washington.
19. Xu J., Tsui B.M.W. Electronic noise modeling in statistical iterative reconstruction. IEEE Trans Image Process 2009, 18:1228-1238.
20. Ma J., Liang Z., Fan Y., Liu Y., Huang J., Chen W., Lu H. Variance analysis of X-ray CT sinograms in the presence of electronic noise background. Med Phys 2012, 39:4051-4065.
21. Whiting B.R. Signal statistics in X-ray computed tomography. SPIE Med Imaging 2002, 4682:53-60.
22. Elbakri L., Fessler J. Efficient and accurate likelihood for iterative image reconstruction in X-ray computed tomography. SPIE Med Imaging 2003, 5032:1839-1850.
23. Whiting B., Massoumzadeh P., Earl O. Properties of preprocessed sinogram data in X-ray CT. Med Phys 2006, 33:3290-3303.
24. La Rivière P.J., Billmire D.M. Reduction of noise-induced streak artifacts in X-ray computed tomography through spline-based penalized-likelihood sinogram smoothing. IEEE Trans Med Imaging 2005, 24:105-111.
25. La Riviere P.J. Penalized-likelihood sinogram smoothing for low-dose CT. Med Phys 2005, 32:1676-1683.
26. Moussouris J. Gibbs and Markov random systems with constraints. J Stat Phys 1974, 10(1):11-33.
27. Besag J. On the statistical analysis of dirty pictures. J R Stat Soc E 1986, 48(3):259-302.
28. Huber P.J., Ronchetti E.M. Robust statistics 2009, Wiley, New York. 2 edition (February 12).
29. Stevenson R., Delp E. Fitting curves with discontinuities. Proc of the 1st Int Workshop on Robust Commt Vision 1990, 127-136.
30. Green P.J. Bayesian reconstructions from emission tomography data using a modified EM algorithm. IEEE Trans Med Imaging 1990, 9:84-93.
31. Lange K. Convergence of EM image reconstruction algorithms with Gibbs priors. IEEE Trans Med Imaging 1990, 9:439-446.
32. Bouman C., Sauer K. A generalized Gaussian image model for edge-preserving MAP estimation. IEEE Trans Image Process 1993, 2:296-310.
33. Charbonnier P., Aubert G., Blanc-Feraud L., Barlaud M. Two deterministic half-quadratic regularization algorithms for computed imaging. Proc. 1st IEEE ICIP 1994.
34. Buades A., Coll B., Morel J. A non-local algorithm for image denoising. IEEE Comput Vis Pattern Recognit 2005, 2:60-65.
35. Buades A., Coll B., Morel J. A review of image denoising algorithms with a new one. Multiscale Model Simul 2005, 4(2):490-530.
36. Giraldo J.C., Kelm Z.S., Guimaraes L.S., Yu L., Fletcher J.G., Erickson B.J., McCollough C.H. Comparative study of two image space noise reduction methods for Computed Tomography: bilateral filter and nonlocal means. 31st Annual International conference for IEEE EMBS 2009.
37. Ma J., Huang J., Feng Q., Zhang H., Lu H., Liang Z., Chen W. Low-dose computed tomography image restoration using previous normal-dose scan. Med Phys 2011, 38:5713-5731.
38. Xu W., Muller K. Efficient low-dose CT artifact mitigation using an artifact-matched prior scan. Med Phys 2012, 39:4748-4760.
39. Buades A., Coll B., Morel J. Image E enhancement by nonlocal reverse heat equation. CMLA 2006.
40. Mignotte M. A non-local regularization strategy for image deconvolution. Pattern Recognit Lett 2008, 29:2206-2212.
41. Chen Y., Ma J., Feng Q., Luo L., Shi P., Chen W. Nonlocal prior Bayesian tomographic reconstruction. J Math Imag Vis 2008, 30(2):133-146.
42. Elmoataz A., Lezoray O., Bougleux S. Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing. IEEE Trans Image Process 2008, 17(7):1047-1060.
43. Lou Y., Zhang X., Osher S., Bertozzi A. Image recovery via nonlocal operators. SIAM J Sci Comput 2010, 42(2):185-197.
44. Zhang X., Burger M., Bresson X., Osher S. Bregmanized nonlocal regularization for deconvolution and sparse reconstruction. SIAM J Imag Sci 2010, 3(3):253-276.
45. Liang D., Wang H., Chang Y., Ying L. Sensitivity encoding reconstruction with nonlocal total variation regularization. Magn Reson Med 2011, 65(5):1384-1392.
46. Tian Z., Jia X., Dong B., Lou Y., Jiang S. Low-dose 4DCT reconstruction via temporal nonlocal means. Med Phys 2011, 38:1359-1365.
47. Wang G., Qi J. Penalized likelihood PET image reconstruction using patch-based edge-preserving regularization. IEEE Trans Med Imaging 2012, 31(12):2194-2204.
48. Ma J., Zhang H., Gao Y., Huang J., Liang Z., Feng Q., Chen W. Iterative image reconstruction for cerebral perfusion CT using a pre-contrast scan induced edge-preserving prior. Phys Med Biol 2012, 57:7519-7542.
49. Yang Z., Jacob M. Nonlocal regularization of inverse problems: a unified variational framework. IEEE Trans Image Process 2013, 22(8):3192-3203.
50. Zhang H., Huang J., Ma J., Bian Z., Feng Q., Lu H., Liang Z., Chen W. Iterative reconstruction for X-ray computed tomography using prior-image induced nonlocal regularization. IEEE Trans Biomed Eng 2014, (in press). 10.1109/TBME.2013.2287244.
51. Thibault J.B., Bouman C., Sauer K., Hsieh J. A recursive filter for noise reduction in statistical iterative tomographic imaging. Proceedings of the SPIE/IS&T Symposium on Electronic Imaging Science and Technology-Computational Imaging, 6065 2006, 15-19.
52. Wang J., Wang S., Li L., Lu H., Liang Z. Virtual colonoscopy screening with ultra low-dose CT: a simulation study. IEEE Trans Nucl Sci 2008, 55:2566-2575.
53. Lu H., Li X., Liang Z. Analytical noise treatment for low-dose CT projection data by penalized weighted least-square smoothing in the K-L domain. SPIE Med Imaging 2002, 4682:146-152.
54. Wang J., Lu H., Eremina D., Zhang G., Wang S., Chen J., Manzione J., Liang Z. An experimental study on the noise properties of X-ray CT sinogram data in the Radon space. Phys Med Biol 2008, 53:3327-3341.
55. Fessler J.A. Penalized weighted least-squares image reconstruction for Positron emission tomography. IEEE Trans Med Imaging 1994, 13:290-300.
56. Segars W.P., Tsui B.M.W. Study of the efficacy of respiratory gating in myocardial SPECT using the new 4-D NCAT phantom. IEEE Trans Nucl Sci 2002, 49(3):675-679.
57. Wang Z., Bovik A. A universal image quality index. IEEE Signal Process Lett 2002, 9:81-84.
58. Bian J., Siewerdsen J.H., Han X., Sidky E.Y., Prince J.L., Pelizzari C., Pan X. Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT. Phys Med Biol 2010, 55:6575-6898.
59. Han X., Bian J., Eaker D.R., Kline T.L., Sidky E.Y., Ritman E.L., Pan X. Algorithm-enabled low-dose micro-CT imaging. IEEE Trans Med Imaging 2011, 30:606-620.
60. Theriault-Lauzier P., Chen G. Characterization of statistical prior image constrained compressed sensing I: applications to time-resolved contrast-enhanced CT. Med Phys 2012, 39(10):5930-5948.
61. Xu F., Mueller K. Accelerating popular tomographic reconstruction algorithms on commodity PC graphics hardware. IEEE Trans Nucl Sci 2005, 52:654-663.
62. Yavuz M., Fessler J.A. Statistical image reconstruction methods for randoms-precorrected PET scans. Med Image Anal 1998, 2(4):369-378.