Prior image constrained compressed sensing (PICCS) and applications in X-ray computed tomography

Current Medical Imaging Reviews

Volumn 6, Issue 2, 2010, Pages 119-134

  Chen, Guang Hong ^a,b   Tang, Jie ^a,b   Nett, Brian ^a,b   Qi, Zhihua ^a,b   Leng, Shuai ^a,b   Szczykutowicz, Timothy ^a,b  

^a UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Compressed sensing; Computed tomography; Image reconstruction

Indexed keywords

ALGORITHM; ANGIOGRAPHY; ARTICLE; CONE BEAM COMPUTED TOMOGRAPHY; DIAGNOSTIC ACCURACY; FOUR DIMENSIONAL ECHOCARDIOGRAPHY; HEART PERFUSION; HUMAN; IMAGE QUALITY; IMAGE RECONSTRUCTION; MATHEMATICAL ANALYSIS; MICRO-COMPUTED TOMOGRAPHY; OPTICAL RESOLUTION; PERFUSION WEIGHTED IMAGING; PRIOR IMAGE CONSTRAINED COMPRESSED SENSING; PRIORITY JOURNAL; RADIATION BEAM; RADIATION DOSE; RADIOGRAPHY; RADIOTHERAPY; X RAY;

EID: 77955813464     PISSN: 15734056     EISSN: None     Source Type: Journal    
DOI: 10.2174/157340510791268498     Document Type: Article

References (101)

1. Peters DC, Korosec FR, Grist TM, et al. Undersampled projection reconstruction applied to MR angiography. Magnet Reson Med 2000; 43(1): 91-101.
2. Vigen KK, Peters DC, Grist TM, Block WF, Mistretta CA. Undersampled projection-reconstruction imaging for time-resolved contrast- enhanced imaging. Magnet Reson Med 2000; 43(2): 170-6.
3. Barger AV, Block WF, Toropov Y, Grist TM, Mistretta CA. Timeresolved contrast-enhanced imaging with isotropic resolution and broad coverage using an undersampled 3D projection trajectory. Magnet Reson Med 2002; 48(2): 297-305.
4. Mistretta CA, Wieben O, Velikina J, et al. Highly constrained backprojection for time-resolved MRI. Magn Reson Med 2006; 55(1): 30-40.
5. Johnson KM, Velikina J, Wu Y, Kecskemeti S, Wieben O, Mistretta CA. Improved waveform fidelity using local HYPR reconstruction (HYPR LR). Magn Reson Med 2008; 59(3): 456-62.
6. Mistretta CA. Undersampled radial MR acquisition and highly constrained back projection (HYPR) reconstruction: potential medical imaging applications in the post-Nyquist era. J Magn Reson Imaging 2009; 29(3): 501-16.
7. Leng S, Zambelli J, Tolakanahalli R, et al. Streaking artifacts reduction in four-dimensional cone-beam computed tomography. Med Phys 2008; 35(10): 4649-59.
8. Sonke JJ, Zijp L, Remeijer P, van Herk M. Respiratory correlated cone beam CT. Med Phys 2005; 32(4): 1176-86.
9. Ruan D, Fessler JA, Balter JM, Sonke JJ. Exploring breathing pattern irregularity with projection-based method. Med Phys 2006; 33(7): 2491-9.
10. Li T, Xing L, Munro P, et al. Four-dimensional cone-beam computed tomography using an on-board imager. Med Phys 2006; 33(10): 3825-33.
11. Li T, Koong A, Xing L. Enhanced 4D cone-beam CT with interphase motion model. Med Phys 2007; 34(9): 3688-95.
12. Lu J, Guerrero TM, Munro P, et al. Four-dimensional cone beam CT with adaptive gantry rotation and adaptive data sampling. Med Phys 2007; 34(9): 3520-9.
13. Leng S, Tang J, Zambelli J, Nett B, Tolakanahalli R, Chen G-H. High temporal resolution and streak-free four-dimensional conebeam computed tomography. Phys Med Biol 2008; 53(20): 5653- 73.
14. Liang ZP, Madore B, Glover GH, Pelc NJ. Fast algorithms for GSmodel- based image reconstruction in data-sharing Fourier imaging. IEEE T Med Imaging 2003; 22(8): 1026-30.
15. Santosa F, Symes WW. Linear inversion of band-limited reflection seismograms. Siam J Sci Stat Comp 1986; 7(4): 1307-30.
16. Santosa F, Symes WW, Raggio G. Inversion of band-limited reflection seismograms using stacking velocities as constraints. Inverse Probl 1987; 3(3): 477-99.
17. Kalender W. Computed Tomography: fundamentals, system technology, image quality, applications. Munich, Germany: MCD Verlag 2002.
18. Candes EJ, Romberg J, Tao T. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inform Theory 2006; 52(2): 489-509.
19. Candes EJ, Tao T. Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans Inform Theory 2006; 52(12): 5406-25.
20. Donoho DL. Compressed sensing. IEEE Trans Inform Theory 2006; 52(4): 1289-306.
21. Trzasko J, Manduca A. Highly undersampled magnetic resonance image reconstruction via homotopic l(0)-minimization. IEEE Trans Med Imaging 2009; 28(1): 106-21.
22. Block KT, Uecker M, Frahm J. Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint. Magn Reson Med 2007; 57(6): 1086-98.
23. Gamper U, Boesiger P, Kozerke S. Compressed sensing in dynamic MRI. Magnet Reson Med 2008; 59(2): 365-73.
24. Lustig M, Donoho D, Pauly JM. Sparse MRI: The application of compressed sensing for rapid MR imaging. Magn Reson Med 2007; 58(6): 1182-95.
25. Jung H, Ye JC, Kim EY. Improved k-t BLAST and k-t SENSE using FOCUSS. Phys Med Biol 2007; 52(11): 3201-26.
26. Provost J, Lesage F. The application of compressed sensing for photo-acoustic tomography. IEEE Trans Med Imaging 2009; 28(4): 585-94.
27. Sidky EY, Kao CM, Pan X. Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT. J X-Ray Sci Technol 2006; 14: 119-39.
28. Tang J, Nett BE, Chen GH. Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms. Phys Med Biol 2009; 54(19): 5781-804.
29. Chen G-H, Tang J, Leng S. Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic ct images from highly undersampled data sets. Med Phys 2008; 35(3): 660-3.
30. Chen G-H, Tang J, Leng S. Prior image constrained compressed sensing (PICCS). Photons Plus Ultrasound: Imaging and Sensing 2008: The Ninth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics; 2008; San Jose, CA, USA: SPIE; 2008; pp. 685618-14.
31. Nett B, Aagaard-Kienitz B, Serarslan Y, Baskaya M, Chen G-H. A simple technique for interventional tool placement combining fluoroscopy with interventional CT on a C-arm system. Neurosurgery 2009; [Epub ahead of print].
32. Chen G-H, Tang J, Nett B, et al. High temporal resolution cardiac cone-beam CT using a slowly rotating C-arm gantry. Proc SPIE Med Imaging 2009; 7258: 72580C.
33. Nett B, Tang J, Leng S, Chen G-H. Tomosynthesis via Total Variation Minimization Reconstruction and Prior Image Constrained Compressed Sensing (PICCS) on a C-arm System. Proc SPIE Med Imaging 2008; 6913: 92672.
34. Chen G-H, Tang J, Hsieh J. Temporal resolution improvement using PICCS in MDCT cardiac imaging. Med Phys 2009; 36(6): 2130-5.
35. Nett B, Tang J, Chen G-H. GPU implementation of Prior Image Constrained Compressed Sensing (PICCS). Proc SPIE Med Imaging 2010; vol. 7622: 762239.
36. Szczykutowicz TP, Hsieh J, Chen G-H. The dependence of image quality on the number of high and low kVp projections in dual energy CT using the Prior Image Constrained Compressed Sensing (PICCS) algorithm. Proc SPIE Med Imaging 2010; [Epub ahead of print].
37. Nett B, Brauweiler R, Kalender W, Rowley H, Chen G-H. Perfusion measurements by micro CT using Prior Image Constrained Compressed Sensing (PICCS): Initial Phantom Results Phys Med Biol 2009; [Epub ahead of print].
38. Nett B, Tang J, Aagaard-Kienitz B, Rowley H, Chen G-H. Low radiation dose C-arm cone-beam CT based on prior image constrained compressed sensing (PICCS): including compensation for image volume mismatch between multiple data acquisitions. Proc SPIE Med Imaging 2009; 7258: 725803.
39. Ramirez Giraldo JC, Trzasko JD, Leng S, McCollough CH, Manduca A. Non-convex prior image constrained compressed sensing (NC-PICCS). Proc SPIE Med Imaging 2010; [Epub ahead of print].
40. Bergner F, Berkus T, Oelhafen M, Kunz P, Pan T, Kachelrieß M. A Comparison of 4D Cone-Beam CT Algorithms for Slowly Rotating Scanners. IEEE NSS/MIC 2009; [cited 25 March 2010] Available from http://www.imp.uni-erlangen.de/IEEE_MIC2009/MIC09_Bergner_M13-210.pdf
41. Candes EJ, Wakin MB, Boyd SP. Enhancing Sparsity by Reweighted ell-1 Minimization. J Fourier Anal Appl 2008; 14(5-6): 877-905.
42. Herman GT. Image Reconstruction from Projections: The Fundamental of Computerized Tomography. New York: Academic Press 1980.
43. Andersen AH, Kak AC. Simultaneous algebraic reconstruction technique (SART): a superior implementation of the art algorithm. Ultrason Imaging 1984; 6(1): 81-94.
44. Press WH. Numerical recipes in C. 2nd ed. New York: Cambridge University Press 1992.
45. Oncel D, Oncel G, Tastan A. Effectiveness of dual-source CT coronary angiography for the evaluation of coronary artery disease in patients with atrial fibrillation: initial experience. Radiology 2007; 245(3): 703-11.
46. Schoenhagen P, Halliburton SS, Stillman AE, et al. Noninvasive imaging of coronary arteries: current and future role of multidetector row CT. Radiology 2004; 232(1): 7-17.
47. Schoepf UJ, Zwerner PL, Savino G, Herzog C, Kerl JM, Costello P. Coronary CT angiography. Radiology 2007; 244(1): 48-63.
48. Vogl TJ, Abolmaali ND, Diebold T, et al. Techniques for the detection of coronary atherosclerosis: multi-detector row CT coronary angiography. Radiology 2002; 223(1): 212-20.
49. Hsieh J. Computed Tomography: principles, Design, artifacts, and recent advances. Bellingham, Washington USA: SPIE Press 2003.
50. Kachelriess M, Knaup M, Kalender WA. Multithreaded cardiac CT. Med Phys 2006; 33(7): 2435-47.
51. Flohr TG, McCollough CH, Bruder H, et al. First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 2006; 16(2): 256-68.
52. Brodoefel H, Burgstahler C, Tsiflikas I, et al. Dual-source CT: effect of heart rate, heart rate variability, and calcification on image quality and diagnostic accuracy. Radiology 2008; 247(2): 346-55.
53. Achenbach S, Anders K, Kalender WA. Dual-source cardiac computed tomography: image quality and dose considerations. Eur Radiol 2008; 18(6): 1188-98.
54. Busch S, Johnson TR, Wintersperger BJ, et al. Quantitative assessment of left ventricular function with dual-source CT in comparison to cardiac magnetic resonance imaging: initial findings. Eur Radiol 2007; 18(3): 570-5.
55. Miller S, Simonetti OP, Carr J, Kramer U, Finn JP. MR Imaging of the heart with cine true fast imaging with steady-state precession: influence of spatial and temporal resolutions on left ventricular functional parameters. Radiology 2002; 223(1): 263-9.
56. Pattynama PM, De Roos A, Van der Wall EE, Van Voorthuisen AE. Evaluation of cardiac function with magnetic resonance imaging. Am Heart J 1994; 128(3): 595-607.
57. Schlosser T, Mohrs OK, Magedanz A, Voigtlander T, Schmermund A, Barkhausen J. Assessment of left ventricular function and mass in patients undergoing computed tomography (CT) coronary angi ography using 64-detector-row CT: comparison to magnetic resonance imaging. Acta Radiol 2007; 48(1): 30-5.
58. Setser RM, Fischer SE, Lorenz CH. Quantification of left ventricular function with magnetic resonance images acquired in real time. J Magn Reson Imaging 2000; 12(3): 430-8.
59. Vedam SS, Keall PJ, Kini VR, Mostafavi H, Shukla HP, Mohan R. Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. Phys Med Biol 2003; 48(1): 45-62.
60. Keall P. 4-dimensional computed tomography imaging and treatment planning. Semin Radiat Oncol 2004; 14(1): 81-90.
61. Keall PJ, Starkschall G, Shukla H, et al. Acquiring 4D thoracic CT scans using a multislice helical method. Phys Med Biol 2004; 49(10): 2053-67.
62. Low DA, Nystrom M, Kalinin E, et al. A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. Med Phys 2003; 30(6): 1254-63.
63. Pan T, Lee TY, Rietzel E, Chen GT. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med Phys 2004; 31(2): 333-40.
64. Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography: image formation and clinical protocol. Med Phys 2005; 32(4): 874-89.
65. Ford NL, Thornton MM, Holdsworth DW. Fundamental image quality limits for microcomputed tomography in small animals. Med Phys 2003; 30(11): 2869-77.
66. Boldea V, Sharp GC, Jiang SB, Sarrut D. 4D-CT lung motion estimation with deformable registration: quantification of motion nonlinearity and hysteresis. Med Phys 2008; 35(3): 1008-18.
67. Lu W, Chen ML, Olivera GH, Ruchala KJ, Mackie TR. Fast freeform deformable registration via calculus of variations. Phys Med Biol 2004; 49(14): 3067-87.
68. Rietzel E, Chen GT. Deformable registration of 4D computed tomography data. Med Phys 2006; 33(11): 4423-30.
69. Schreibmann E, Thorndyke B, Li T, Wang J, Xing L. Fourdimensional image registration for image-guided radiotherapy. Int J Radiat Oncol Biol Phys 2008; 71(2): 578-86.
70. Yang DL, Lu W, Low DA, et al. 4D-CT motion estimation using deformable image registration and 5D respiratory motion modeling. Med Phys 2008; 35(10): 4577-90.
71. Zhang T, Orton NP, Tome WA. On the automated definition of mobile target volumes from 4D-CT images for stereotactic body radiotherapy. Med Phys 2005; 32(11): 3493-502.
72. Lu W, Ruchala KJ, Chen ML, Chen Q, Olivera GH. Real-time respiration monitoring using the radiotherapy treatment beam and four-dimensional computed tomography (4DCT)-a conceptual study. Phys Med Biol 2006; 51(18): 4469-95.
73. Li T, Schreibmann E, Yang Y, Xing L. Motion correction for improved target localization with on-board cone-beam computed tomography. Phys Med Biol 2006; 51(2): 253-67.
74. Li T, Xing L. Optimizing 4D cone-beam CT acquisition protocol for external beam radiotherapy. Int J Radiat Oncol Biol Phys 2007; 67(4): 1211-9.
75. Yang Y, Schreibmann E, Li T, Wang C, Xing L. Evaluation of onboard kV cone beam CT (CBCT)-based dose calculation. Phys Med Biol 2007; 52(3): 685-705.
76. Kak C, Slaney M. Principles of computerized tomography. Piscatway, NJ: IEEE Press 1987.
77. Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am a-Optics Image Sci Vision 1984; 1(6): 612-9.
78. Zijp L, Sonke JJ, van Herk M. Extraction of the respiratory signal from sequential thorax cone-beam x-ray images. Proc 14th ICC. Seoul, Korea, 2004: pp. 507-9.
79. Chen G-H, Zambelli J, Nett B, E, et al. Design and development of C-arm based cone-beam CT for image-guided interventions: initial results. In: Michael JF, Jiang H, Eds. SPIE; 2006; pp. 614210.
80. Daly MJ, Siewerdsen JH, Moseley DJ, Jaffray DA, Irish JC. Intraoperative cone-beam CT for guidance of head and neck surgery: Assessment of dose and image quality using a C-arm prototype. Med Phys 2006; 33(10): 3767-80.
81. Fahrig R, Dixon R, Payne T, Morin RL, Ganguly A, Strobel N. Dose and image quality for a cone-beam C-arm CT system. Med Phys 2006; 33(12): 4541-50.
82. Siewerdsen JH, Moseley DJ, Burch S, et al. Volume CT with a flatpanel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. Med Phys 2005; 32(1): 241-54.
83. Fahrig R, Fox AJ, Lownie S, Holdsworth DW. Use of a C-arm system to generate true three-dimensional computed rotational angiograms: preliminary in vitro and in vivo results. Am J Neuroradiol 1997; 18(8): 1507-14.
84. Lauritsch G, Boese J, Wigstrom L, Kemeth H, Fahrig R. Towards cardiac C-arm computed tomography. IEEE Trans Med Imaging 2006; 25(7): 922-34.
85. Ritman EL, Bolander ME, Fitzpatrick LA, Turner RT. Micro-CT imaging of structure-to-function relationship of bone microstructure and associated vascular involvement. Technol Health Care 1998; 6(5-6): 403-12.
86. Thali MJ, Taubenreuther U, Karolczak M, et al. Forensic microradiology: micro-computed tomography (Micro-CT) and analysis of patterned injuries inside of bone. J Forensic Sci 2003; 48(6): 1336- 42.
87. Wang Y, Wertheim DF, Jones AS, Coombes AG. Micro-CT in drug delivery. Eur J Pharm Biopharm 2009; 74(1): 41-9.
88. Engelke K, Karolczak M, Lutz A, Seibert U, Schaller S, Kalender W. Micro-CT. Technology and application for assessing bone structure. Radiologe 1999; 39(3): 203-12.
89. Ritman EL. Micro-computed tomography of the lungs and pulmonary-vascular system. Proc Am Thorac Soc 2005; 2(6): 477-80.
90. Eastwood JD, Lev MH, Azhari T, et al. CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke. Radiology 2002; 222(1): 227-36.
91. Klotz E, Konig M. Perfusion measurements of the brain: using dynamic CT for the quantitative assessment of cerebral ischemia in acute stroke. Eur J Radiol 1999; 30(3): 170-84.
92. Koenig M, Klotz E, Luka B, Venderink DJ, Spittler JF, Heuser L. Perfusion CT of the brain: diagnostic approach for early detection of ischemic stroke. Radiology 1998; 209(1): 85-93.
93. Miles KA, Eastwood JD, Konig M. Multidetector computed tomography in cerebrovascular disease, CT perfusion imaging. Andover: Thomson Publishing 2007.
94. Nabavi DG, Cenic A, Craen RA, et al. CT assessment of cerebral perfusion: experimental validation and initial clinical experience. Radiology 1999; 213(1): 141-9.
95. Kachelriess M, Knaup M, Bockenbach O. Hyperfast parallel-beam and cone-beam backprojection using the cell general purpose hardware. Med Phys 2007; 34(4): 1474-86.
96. Mueller K, Yagel R. Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware. IEEE Trans Med Imaging 2000; 19(12): 1227-37.
97. Xu F, Mueller K. Accelerating popular tomographic reconstruction algorithms on commodity PC graphics hardware. IEEE Trans Nucl Sci 2005; 52: 654-63.
98. Xu F, Mueller K. Real-time 3D computed tomographic reconstruction using commodity graphics hardware. Phys Med Biol 2007; 52(12): 3405-19.
99. Yang H, Li M, Koizumi K, Kudo H. Accelerating Backprojections via CUDA Architecture. 9th International Meeting on Fully 3D Image Reconstruction 2007: 52-5.
100. Alvarez RE, Macovski A. Energy-selective reconstructions in x-ray computerized tomography. Phys Med Biol 1976; 21: 1976.
101. Kelcz F, Joseph PM, Hilal SK. Noise considerations in dual energy CT scanning. Med Phys 1979; 6: 418-25.