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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 760903, 8 pages
http://dx.doi.org/10.1155/2013/760903
Research Article

Improving the Convergence Rate in Affine Registration of PET and SPECT Brain Images Using Histogram Equalization

Department of Signal Theory Networking and Communication, University of Granada, ETSIIT, 18071 Granada, Spain

Received 15 February 2013; Accepted 12 April 2013

Academic Editor: Anke Meyer-Baese

Copyright © 2013 D. Salas-Gonzalez 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. L. S. Yin, L. Tang, G. Hamarneh et al., “Complexity and accuracy of image registration methods in SPECT-guided radiation therapy.,” Physics in medicine and biology, vol. 55, no. 1, pp. 237–246, 2010. View at Google Scholar · View at Scopus
  2. D. Salas-Gonzalez, J. M. Górriz, J. Ramírez, A. Lassl, and C. G. Puntonet, “Improved Gauss-Newton optimisation methods in affine registration of SPECT brain images,” Electronics Letters, vol. 44, no. 22, pp. 1291–1292, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. D. B. Stout, E. Komisopoulou, A. F. Chatziioannou, and P. L. Chow, “A method of image registration for small animal, multi-modality imaging,” Physics in Medicine and Biology, vol. 51, no. 2, pp. 379–390, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Zagorchev and A. Goshtasby, “A comparative study of transformation functions for nonrigid image registration,” IEEE Transactions on Image Processing, vol. 15, no. 3, pp. 529–538, 2006. View at Publisher · View at Google Scholar · View at Scopus
  5. P. A. Freeborough, R. P. Woods, and N. C. Fox, “Accurate registration of serial 3D MR brain images and its application to visualizing change in neurodegenerative disorders,” Journal of Computer Assisted Tomography, vol. 20, no. 6, pp. 1012–1022, 1996. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Holden, D. L. G. Hill, E. R. E. Denton et al., “Voxel similarity measures for 3d serial mr image registration,” IEEE Transactions in Medical Imaging, vol. 19, pp. 94–102, 2000. View at Google Scholar
  7. S. Chang, B. Davis, E. Chaney, N. Strehl, M. Foskey, and L. Goyal, “Large deformation three-dimensional image registration in image-guided radiation therapy,” Physics in Medicine and Biology, vol. 50, no. 24, pp. 5869–5892, 2005. View at Publisher · View at Google Scholar · View at Scopus
  8. B. Zitová and J. Flusser, “Image registration methods: A survey,” Image and Vision Computing, vol. 21, no. 11, pp. 977–1000, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. D. L. G. Hill, P. G. Batchelor, M. Holden, and D. J. Hawkes, “Medical image registration,” Physics in Medicine and Biology, vol. 46, no. 3, pp. R1–R45, 2001. View at Publisher · View at Google Scholar · View at Scopus
  10. P. M. Thompson and A. W. Toga, “The role of image registration in brain mapping,” Image and Vision Computing, vol. 19, no. 1-2, pp. 3–24, 2001. View at Google Scholar · View at Scopus
  11. S. Vandenberghea, Y. D'Asselera, R. V. de Wallea et al., “Iterative reconstruction algorithms in nuclear medicine,” Computerized Medical Imaging and Graphics, vol. 25, pp. 105–111, 2001. View at Google Scholar
  12. P. P. Bruyant, “Analytic and iterative reconstruction algorithms in SPECT,” Journal of Nuclear Medicine, vol. 43, no. 10, pp. 1343–1358, 2002. View at Google Scholar · View at Scopus
  13. J. Zhou and L. M. Luo, “Sequential weighted least squares algorithm for PET image reconstruction,” Digital Signal Processing, vol. 16, no. 6, pp. 735–745, 2006. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Ramírez, J. M. Górriz, M. Gomez-Río et al., “Effective emission tomography image reconstruction algorithms for spect data,” in Proceedings of the International Conference on Computational Science (ICCS '08), vol. 5101 of Lecture Notes in Computer Science, pp. 741–748, Springer, Berlin, Germany, 2008. View at Google Scholar
  15. R. P. Woods, S. T. Grafton, C. J. Holmes, S. R. Cherry, and J. C. Mazziotta, “Automated image registration: I. General methods and intrasubject, intramodality validation,” Journal of Computer Assisted Tomography, vol. 22, no. 1, pp. 139–152, 1998. View at Publisher · View at Google Scholar · View at Scopus
  16. P. Thevenaz, T. Blu, and M. Unser, “Image interpolation and resamplingin,” in Handbook of Medical Imaging, Processing and Analysis, I. N. Bankman, Ed., pp. 393–420, Academic Press, San Diego, Calif, USA, 2000. View at Google Scholar
  17. P. Thevenaz, T. Blu, and M. Unser, “Interpolation revisited,” IEEE Transactions on Medical Imaging, vol. 19, no. 7, pp. 739–758, 2000. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Nocedal and S. J. Wright, Numerical Optimization, Springer, New York, NY, USA, 1999.