Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2011, Article ID 173748, 9 pages
http://dx.doi.org/10.1155/2011/173748
Research Article

Efficient CT Metal Artifact Reduction Based on Fractional-Order Curvature Diffusion

1College of Computer Science, Sichuan University, Chengdu 610065, China
2School of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China

Received 13 April 2011; Revised 20 May 2011; Accepted 26 May 2011

Academic Editor: Dimos Baltas

Copyright © 2011 Yi Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Hsieh, Computed Tomography: Principles, Design, Artifacts, and Recent Advances, SPIE Press, Bellingham, Wash, USA, 2003.
  2. P. Stradiotti, A. Curti, G. Castellazzi, and A. Zerbi, “Metal-related artifacts in instrumented spine. techniques for reducing artifacts in CT and MRI: state of the art,” European Spine Journal, vol. 18, supplement 1, pp. S102–S108, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Kondo, Y. Hayakawa, J. Dong, and A. Honda, “Iterative correction applied to streak artifact reduction in an X-ray computed tomography image of the dento-alveolar region,” Oral Radiology, vol. 26, no. 1, pp. 61–65, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Yazdia, L. Gingras, and L. Beaulieu, “An adaptive approach to metal artifact reduction in helical computed tomography for radiation therapy treatment planning: experimental and clinical studies,” International Journal of Radiation Oncology Biology Physics, vol. 62, no. 4, pp. 1224–1231, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. N. A. Ebraheim, R. Coombs, J. J. Rusin, and W. T. Jackson, “Reduction of postoperative CT artifacts of pelvic fractures by use of titanium implants,” Orthopedics, vol. 13, no. 12, pp. 1357–1358, 1990. View at Google Scholar · View at Scopus
  6. N. Haramati, R. B. Staron, K. Mazel-Sperling et al., “CT scans through metal scanning technique versus hardware composition,” Computerized Medical Imaging and Graphics, vol. 18, no. 6, pp. 429–434, 1994. View at Publisher · View at Google Scholar
  7. R. M. Lewitt and R. H. Bates, “Image reconstruction from projections(III): projection completion methods,” Optik, vol. 50, no. 4, pp. 189–204, 1978. View at Google Scholar · View at Scopus
  8. W. A. Kalender, R. Hebel, and J. Ebersberger, “Reduction of CT artifacts caused by metallic implants,” Radiology, vol. 164, no. 2, pp. 576–577, 1987. View at Google Scholar · View at Scopus
  9. C. R. Crawford, “Reprojection using a parallel backprojector,” Medical Physics, vol. 13, no. 4, pp. 480–483, 1986. View at Google Scholar · View at Scopus
  10. J. W. Gu, L. Zhang, Z. Q. Chen, Y. X. Xing, and Z. F. Huang, “A method based on interpolation for metal artifacts reduction in CT images,” Journal of X-Ray Science and Technology, vol. 14, no. 1, pp. 11–19, 2006. View at Google Scholar · View at Scopus
  11. S. Zhao, D. D. Robertson, G. Wang, B. Whiting, and K. T. Bae, “X-ray CT metal artifact reduction using wavelets: an application for imaging total hip prostheses,” IEEE Transactions on Medical Imaging, vol. 19, no. 12, pp. 1238–1247, 2000. View at Google Scholar · View at Scopus
  12. J. Gu, L. Zhang, G. Yu, Y. Xing, and Z. Chen, “X-ray CT metal artifacts reduction through curvature based sinogram inpainting,” Journal of X-Ray Science and Technology, vol. 14, no. 2, pp. 73–82, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. X. Duan, L. Zhang, Y. Xiao, J. Cheng, Z. Chen, and Y. Xing, “Metal artifact reduction in CT images sinogram TV inpainting,” in Proceedings of the IEEE Nuclear Science Symposium Conference Record (NSS/MIC '08), pp. 4175–4177, Dresden, Germany, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. B. de Man, J. Nuyts, P. Dupont, G. Marchal, and P. Suetens, “An iterative maximum-likelihood polychromatic algorithm for CT,” IEEE Transactions on Medical Imaging, vol. 20, no. 10, pp. 999–1008, 2001. View at Google Scholar · View at Scopus
  15. G. Wang, D. L. Snyder, J. A. O'Sullivan, and M. W. Vannier, “Iterative deblurring for metal artifact reduction,” IEEE Transactions on Medical Imaging, vol. 15, no. 5, pp. 657–667, 1996. View at Google Scholar · View at Scopus
  16. C. Lemmens, D. Faul, and J. Nuyts, “Suppression of metal artifacts in CT using a reconstruction procedure that combines MAP and projection completion,” IEEE Transactions on Medical Imaging, vol. 28, no. 2, Article ID 4591397, pp. 250–260, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. D. Prell, Y. Kyriakou, M. Beister, and W. A. Kalender, “A novel forward projection-based metal artifact reduction method for flat-detector computed tomography,” Physics in Medicine and Biology, vol. 54, no. 21, pp. 6575–6591, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. Y. Zhang, Y. Pu, J. Hu, and J. Zhou, “A fractional framework for image inpainting,” submitted to IET Image Process.
  19. T. F. Chan and J. Shen, “Mathematical models for local nontexture inpaintings,” SIAM Journal on Applied Mathematics, vol. 62, no. 3, pp. 1019–1043, 2001. View at Publisher · View at Google Scholar · View at Scopus
  20. L. I. Rudin, S. Osher, and E. Fatemi, “Nonlinear total variation based noise removal algorithms,” Physica D, vol. 60, no. 1–4, pp. 259–268, 1992. View at Google Scholar · View at Scopus
  21. Z. Jun and W. Zhihui, “A class of fractional-order multi-scale variational models and alternating projection algorithm for image denoising,” Applied Mathematical Modelling, vol. 35, pp. 2516–2528, 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. T. F. Chan and J. Shen, “Nontexture inpainting by curvature-driven diffusions,” Journal of Visual Communication and Image Representation, vol. 12, no. 4, pp. 436–449, 2001. View at Publisher · View at Google Scholar · View at Scopus
  23. K. B. Oldham and J. Spanie, The Fractional Calculus, Academic Press, New York, NY, USA, 1974.
  24. Y. Pu, W. Wang, J. Zhou, H. Jia, and Y. Wang, “Fractional derivative detection of digital image texture details and implementation of fractional derivative filter,” Science in China Series F, vol. 38, no. 12, pp. 2252–2272, 2008. View at Google Scholar
  25. Y. F. Pu, J. L. Zhou, and X. Yuan, “Fractional differential mask: a fractional differential-based approach for multiscale texture enhancement,” IEEE Transactions on Image Processing, vol. 19, no. 2, Article ID 5340520, pp. 491–511, 2010. View at Publisher · View at Google Scholar · View at Scopus
  26. J. C. Russ, The Image Processing Handbook, CRC Press, Boca Raton, Fla, USA, 6th edition, 2011.
  27. M. Bertalmío, A. Bertozzi, and G. Sapiro, “Navier-Stokes, fluid dynamics, and image and video inpainting,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (CVPR '01), pp. 355–362, December 2001. View at Scopus
  28. M. Bertalmío, “Strong-continuation, contrast-invariant inpainting with a third-order optimal PDE,” IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1934–1938, 2006. View at Publisher · View at Google Scholar · View at Scopus