Table of Contents
ISRN Biomathematics
Volume 2013, Article ID 534891, 6 pages
http://dx.doi.org/10.1155/2013/534891
Research Article

Total Variation Filtered Demons for Improved Registration of Sliding Organs

1Department of Electrical and Computer Engineering, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina
2Medical Image Analysis Center, University of Basel, 4031 Basel, Switzerland

Received 16 September 2013; Accepted 10 November 2013

Academic Editors: J. Chow and X. Wan

Copyright © 2013 Damir Demirović 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. A. J. B. Maintz and M. A. Viergever, “A survey of medical image registration,” Medical Image Analysis, vol. 2, no. 1, pp. 1–36, 1998. View at Google Scholar · View at Scopus
  2. B. K. P. Horn and B. G. Schunk, “Determining optical flow,” Artifical Inteligence, vol. 17, pp. 1185–3203, 1981. View at Google Scholar
  3. M. Von Siebenthal, G. Székely, U. Gamper, P. Boesiger, A. Lomax, and P. Cattin, “4D MR imaging of respiratory organ motion and its variability,” Physics in Medicine and Biology, vol. 52, no. 6, article 1, pp. 1547–1564, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Kiriyanthan, K. Fundana, and P. C. Cattin, “Discontinuity preserving registration of abdominal MR images with apparent sliding organ motion,” in Abdominal Imaging. Computational and Clinical Applications, vol. 7029, pp. 231–239, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. D. Ruan, J. A. Fessler, and S. Esedoglu, “Discontinuity preserving regularization for modeling sliding in medical image registration,” in Proceedings of the IEEE Nuclear Science Symposium Conference Record (NSS/MIC '08), pp. 5304–5308, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. M. P. Heinrich, M. Jenkinson, M. Brady, and J. A. Schnabel, “Discontinuity preserving regularization for variational optical- ow registration using the modified L-p norm,” in Proceedings of the MICCAI Workshop on Evaluation of Methods for Pulmonary Image Registration (EMPIRE '10), 2010.
  7. K. Ding, Y. Yin, K. Cao et al., “Evaluation of lobar biomechanics during respiration using image registration,” in Proceedings of the 12th International Conference, Medical Image Computing and Computer-Assisted Intervention (MICCAI '09), pp. 739–746, London, UK, 2009.
  8. A. Schmidt-Richberg, J. Ehrhardt, R. Werner, and H. Handels, “Slipping objects in image registration: improved motion field estimation with direction-dependent regularization,” in Proceedings of the Medical Image Computing and Computer-Assisted Intervention (MICCAI '09), vol. 5761, no. 1, pp. 755–762, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. D. F. Pace, A. Enquobahrie, H. Yang, S. R. Aylward, and M. Niethammer, “Deformable image registration of sliding organs using anisotropic diffusive regularization,” in Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI '11), pp. 407–413, usa, April 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. J.-P. Thirion, “Image matching as a diffusion process: an analogy with Maxwell's demons,” Medical Image Analysis, vol. 2, no. 3, pp. 243–260, 1998. View at Google Scholar · View at Scopus
  11. H. Wang, L. Dong, J. O'Daniel et al., “Validation of an accelerated “demons” algorithm for deformable image registration in radiation therapy,” Physics in Medicine and Biology, vol. 50, no. 12, pp. 2887–2905, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. P. Cachier, X. Pennec, and N. Ayache, “Fast non-rigid matching by gradient descent: study and improvement of the “Demons” algorithm,” Tech. Rep. RR-3706.
  13. 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
  14. A. Wedel, T. Pock, C. Zach, H. Bischof, and D. Cremers, “An improved algorithm for TV-L1 optical flow,” in Statistical and Geometrical Approaches to Visual Motion Analysis, pp. 23–45, Springer, Berlin, Germany, 2009. View at Google Scholar
  15. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill Posed Problems, Edited by F. John, V. H. Winston and Sons, New York, NY, USA, 1977.
  16. A. Chambolle, “An Algorithm for Total Variation Minimization and Applications,” Journal of Mathematical Imaging and Vision, vol. 20, no. 1-2, pp. 89–97, 2004. View at Publisher · View at Google Scholar · View at Scopus