Statistical Image Reconstruction for Inconsistent CT Projection Data

Summary

Objectives: The filtered backprojection is not able to cope with metal-induced inconsistencies in the Radon space which leads to artifacts in reconstructed CT images. A new algorithm is presented that reduces the drawbacks of existing artifact reduction strategies.

Methods: Inconsistent projection data are bridged by directed interpolation. These projections are reconstructed using a weighted maximum likelihood algorithm (λ-MLEM). The correlation coefficient between images of a torso phantom marked with steel markers reconstructed with λ-MLEM and images of the same torso slice without markers quantifies the quality achieved. For clinical data, entropy maximization is presented to obtain appropriate weightings.

Results: Different interpolation strategies have been applied. The quality of reconstruction sensitively depends on the complexity of interpolation. A directional interpolation gives best results. However, the quality of the images can be further improved byan appropriate weighing within λ-MLEM. This has been demonstrated with data from a torso phantom, a jaw with amalgam fillings and a hip prosthesis.

Conclusions: λ-MLEM image reconstruction using data from directional Radon space interpolation is a new approach for metal artifact reduction. The weighting in this statistical approach is used to reduce the influence of residual inconsistencies in a way that optimal artifact suppression is obtained by optimizing a compromise between residual inconsistencies and void data. The image quality is superior compared with other artifact reduction strategies.

Keywords

Transmission computed tomography - artifacts - computer-assisted image processing - image reconstruction

• References

• 1 Duerinckx AJ, Markovski A. Nonlinear Polychromatic and Noise Artifacts in X-Ray Computed Tomography Images. J Comput Assist Tomogr 1979; 03: 519-526.
• 2 Duerinckx AJ, Macovski A. Polychromatic Streak Artifacts in Computed Tomography Images. J Comput Assist Tomogr 1978; 02: 481-487.
• 3 Joseph PM, Spital RD. A Method for Correcting Bone Induced Artifacts in Computed Tomography Scanners. J Comput Assist Tomogr 1978; 02: 100-108.
• 4 Robertson DD, Huang HK. Quantitative bone measurements using x-ray computed tomography with second order correction. Med Phys 1986; 13: 474-479.
• 5 Meagher JM, Mote CD, Skinner HB. CT Image Correction for Beam Hardening Using Simulated Projection Data. IEEE Trans on Nucl Sci 1990; 37: 1520-1524.
• 6 Joseph PM, Ruth C. A method for simultaneous correction of spectrum hardening artefacts in CT images containing both bone and iodine. Med Phys 1997; 24: 1629-1634.
• 7 Kachelrieß M. Reduction of Metal Artifacts in X-Ray Computed Tomography (in German) (dissertation). Erlangen-Nürnberg: Friedrich-Alexander-University; 1998
• 8 De Man B, Nuyts J, Dupont P, Marchal G, Suetens P. Metal Streak Artifacts in X-ray Computed Tomography: A Simulation Study IEEE Trans Nucl Sci. 1999; 46: 691-696.
• 9 De Man B. Iterative Reconstruction for Reduction of Metal Artifacts in Computed Tomography (dissertation). University of Leuven; 2001
• 10 Joseph PM, Spital RD. The exponential edge-gradient effect in x-ray computed tomography. Phys Med Biol 1980; 26: 473-487.
• 11 Glover GH, Pelc NH. An algorithm for the reduction of metal clip artifacts in CT reconstructions. Med Phys 1981; 08: 799-807.
• 12 Joseph PM, Spital RD, Stockham CD. The effects of sampling on CT images. Comput Tomogr 1980; 04: 189-206.
• 13 Joseph PM, Schulz RA. View sampling requirements in fan beam computed tomography. Med Phys 1980; 07: 692-702.
• 14 Glover GH, Pelc NJ. Nonlinear partial volume artefacts in x-ray computed tomography. Med Phys 1980; 07: 238-248.
• 15 Lange K, Carson R. EM reconstruction algorithms for emission and transmission tomography. J Comput Assist Tomogr 1984; 08: 306-316.
• 16 Kalender WA, Hebel R, Ebersberger J. Reduction of CT artifacts caused by metallic implants. Radiology 1987; 164: 576-577.
• 17 Lewis RM, Bates RHT. Image reconstruction from projections III: Projection completion methods (theory). Optik 1978; 50: 189-204.
• 18 Medoff BP, Brody WR, Nassi M, Macovski A. Iterative convolution backprojection algorithms for image reconstruction from limited data. J Opt Soc Am 1983; 73: 1493-1500.
• 19 Hinderling T, Rüegsegger P, Anliker M, Dietsschi C. Computed Tomography Reconstruction from Hollow Projections: An Application to In Vivo Evaluation of Artificial Hip Joints. J Comp Assist Tomogr 1979; 03: 52-57.
• 20 Klotz E, Kalender WA, Sokiranski R, Felsenberg D. Algorithms for reduction of CT artifacts caused by metallic implants. Proceedings SPIE 1990; 1234: 642-650.
• 21 Seitz P, Rüegsegger P. Anchorage of Femoral Implants Visualized by Modified Computed Tomography. Arch Orthop Trauma Surg 1982; 100: 261-266.
• 22 Seitz P, Rüegsegger P. CT bone densitometry of the anchorage of artificial knee joints. J Comp Assist Tomogr 1985; 09: 621-622.
• 23 Tuy HK. A post-processing algorithm to reduce metallic clip artifacts in CT images. Eur Radiol 1981; 03: 129-134.
• 24 Lonn AHR, Crawford CR. Reduction of artefacts caused by metallic objects in CT. Radiology 1988; 169: 116.
• 25 Zerfowski D. Compensation of Metal Artifacts in Computed Tomography (in German). Proceedings of the Workshop: Bildverarbeitung für die Medizin 1998. Informatik Aktuell. Springer; 1998
• 26 Zhao S, Robertson DD, Wang G, Whiting B, Bae K. X-Ray CT Metal Artifact Reduction Using Wavelets: An Application for Imaging Total Hip Prostheses. IEEE Trans Med Imaging 2000; 19: 1238-1247.
• 27 August J. Decoupling the Equations of Regularized Tomography. Proceedings of the IEEE International Symposium on Biomedical Imaging. 2002: 653-656.
• 28 Robertson DD, Yuan J, Wang G, Vannier MW. Total Hip Prosthesis Metal-Artifact Suppression Using Iterative Deblurring Reconstruction. J Comput Assist Tomogr 1997; 21: 293-298.
• 29 Wang G, Snyder DL, O’Sullivan JA, Vannier MW. Iterative deblurring for CT metal artefact reduction. IEEE Trans Med Imaging 1996; 15: 657-664.
• 30 Oppenheim BE. Reconstruction tomography from incomplete projections. Ter-Pogossian M. Reconstruction Tomography in Diagnostic Radiology and Nuclear Medicine. Baltimore, MD: University Park; 1977: 155-183.
• 31 Snyder DL, O’Sullivan JA, Whiting BR, Murphy RJ, Benac J, Cataldo JA, Politte DG, Williamson JF. Deblurring subject to nonnegativity constraints when known functions are present, with application to object-constrained computerized tomography. IEEE Trans Med Imaging 2001; 20: 1009-1017.
• 32 Philips Medical System. Service Manual System Tomoscan M/EG MCT 3501/MCT 3902. 1996
• 33 CIRS Incorporated Tissue Simulation and Phantom Technology (homepage on the Internet). Computerized Imaging Reference Systems, Inc.; c2005 (updated 2005; cited Sep 30, 2006). Available from: http://www.cirsinc.com/602_ct_xray.html.
• 34 Bertram M, Rose G, Schäfer D, Wiegert J, Aach T. Directional interpolation of sparsely sampled cone-beam CT sinogram data. Proceedings of the IEEE International Symposium on Biomedical Imaging. 2004: 928-931.
• 35 Bertalmio M, Sapira G. Image Inpainting. Computer Graphics. SIGGRAPH2000. 2000: 417-24.
• 36 Shepp LA, Vardi Y. Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging 1982; 01: 113-121.
• 37 Press WH, Flannery BP, Teukolsky SA, Vetterling WT. Numerical Recipes in C: The Art of Scientific Computing. Cambridge: Cambridge University Press; 1990
• 38 Geman S, Mc Clure D. Bayesian image analysis: An application to single photon emission tomography. Proceedings of Stat Comp Sect of Amer Stat Assoc; 1985.. Washington D.C.: 1985: 12-18.
• 39 Geman S, Geman D. Stochastic Relaxation, Gibbs Distributions and the Bayesian Restoration of Images. IEEE Trans on Patt Anal and Mach Intel 1984; 06: 721-741.
• 40 Fessler JA. Penalized Weighted Least-Squares Image Reconstruction for Positron Emission Tomography. IEEE Trans Med Imaging 1984; 13: 290-300.
• 41 De Man B, Nuyts J, Dupont P, Marchai G, Suetens E. Reduction of metal streak artefacts in x-ray computed tomographyusingatransmission maximum a posteriori algorithm. IEEE Trans Nucl Sci 2003; 47: 977-981.
• 42 Green PJ. Bayesian reconstruction from emission tomography data using a modified EM algorithm. IEEE Trans Med Imaging 1990; 09: 84-93.
• 43 De Man B, Basu S. Generalized Geman prior for iterative reconstruction. Proceedings of Biomedizinische Technik 2005; 50 (01) 358-359.
• 44 Lange K, Fessler JA. Globally convergent algorithm for maximum a posteriori transmission tomography. IEEE Trans Image Process 1995; 04: 1430-1438.
• 45 Bouman CA, Sauer K. A Unified Approach to Statistical Tomography Using Coordinate Descent Optimization. IEEE Trans Med Imaging 1996; 05: 480-491.
• 46 Sauer K, Bouman C. A Local Update Strategy for iterative Reconstructions from projections. IEEE Trans Signal Process 1993; 41: 534-548.
• 47 Lange K. Convergence of EM Image Reconstruction Algorithms with Gibbs Priors. IEEE Trans Med Imaging 1990; 09: 439-446.