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International Journal of Biomedical Imaging
Volume 2010 (2010), Article ID 425891, 11 pages
http://dx.doi.org/10.1155/2010/425891
Research Article

MRI Superresolution Using Self-Similarity and Image Priors

1Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain
2McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada H3A 2B4
3Mathématiques et Informatique, Université Paris Descartes, 45 Rue des Saints Pères, 75270 Paris Cedex 06, France
4Department de Matemàtiques i Informàtica, Universitat Illes Balears, Ctra Valldemossa km 7.5, 07122 Palma de Mallorca, Spain

Received 21 April 2010; Accepted 1 October 2010

Academic Editor: Ge Wang

Copyright © 2010 José V. Manjón 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. M. S. Atkins, K. Siu, B. Law, J. Orchard, and W. Rosenbaum, “Difficulties of T1 brain MRI segmentation techniques,” in The International Society for Optical Engineering, vol. 4684 of Proceedings of SPIE, pp. 1837–1844, 2002. View at Publisher · View at Google Scholar
  2. E. Vansteenkiste, J. Vandemeulebroucke, and W. Philips, “2D/3D registration of neonatal brain images,” in Proceedings of the The Workshop on Biomedical Image Registration (WBIR '06), pp. 272–279, 2006.
  3. P. Thévenaz, 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
  4. T. M. Lehmann, C. Gönner, and K. Spitzer, “Survey: interpolation methods in medical image processing,” IEEE Transactions on Medical Imaging, vol. 18, no. 11, pp. 1049–1075, 1999. View at Publisher · View at Google Scholar · View at Scopus
  5. E. Carmi, S. Liu, N. Alon, A. Fiat, and D. Fiat, “Resolution enhancement in MRI,” Magnetic Resonance Imaging, vol. 24, no. 2, pp. 133–154, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. P. Kornprobst, R. Peelers, M. Nikolova, R. Deriche, M. Ng, and P. Van Hecke, “A superresolution framework for fMRI sequences and its impact on resulting activation maps,” in Proceedings 6th International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI '03), vol. 2879, pp. 117–125, November 2003. View at Scopus
  7. S. Peled and Y. Yeshurun, “Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging,” Magnetic Resonance in Medicine, vol. 45, no. 1, pp. 29–35, 2001. View at Publisher · View at Google Scholar · View at Scopus
  8. F. Rousseau, “Brain hallucination,” in Proceedings of the European Conference on Computer Vision (ECCV '08), LNCS, pp. 497–508, Springer, New York, NY, USA, 2008.
  9. A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '05), vol. 2, pp. 60–65, June 2005. View at Scopus
  10. J. Sijbers, Signal and noise estimation from magnetic resonance images, Doctoral thesis, Antwepen, Belgium, 1998.
  11. J. Banerjee and C. V. Jawahar, “Super-resolution of text images using edge-directed tangent field,” in Proceedings of the 8th IAPR International Workshop on Document Analysis Systems (DAS '08), pp. 76–83, September 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. P. Coupé, P. Yger, S. Prima, P. Hellier, C. Kervrann, and C. Barillot, “An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images,” IEEE Transactions on Medical Imaging, vol. 27, no. 4, Article ID 4359947, pp. 425–441, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. N. Wiest-Daesslé, S. Prima, P. Coupé, S. P. Morrissey, and C. Barillot, “Rician noise removal by non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT-MRI,” in Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 171–179, New York, NY, USA, 2008.
  14. L. P. Yaroslavsky, Digital Picture Processing. An Introduction, Springer, Berlin, Germany, 1985.
  15. C. A. Cocosco, V. Kollokian, R. K.-S. Kwan, and A. C. Evans, “Brain web: online interface to a 3D MRI simulated brain database,” in Proceedings of 3rd International Conference on Functional Mapping of the Human Brain, vol. 5, 1997.
  16. D. L. Collins, A. P. Zijdenbos, V. Kollokian et al., “Design and construction of a realistic digital brain phantom,” IEEE Transactions on Medical Imaging, vol. 17, no. 3, pp. 463–468, 1998. View at Google Scholar · View at Scopus
  17. A. Buades, B. Coll, J.-M. Morel, and C. Sbert, “Self-similarity driven color demosaicking,” IEEE Transactions on Image Processing, vol. 18, no. 6, pp. 1192–1202, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Hajnal, D. L. G. Hill, and D. J. Hawkes, Medical Image Registration, CRC Press, London, UK, 2001.
  19. J. Ashburner and K. J. Friston, “Unified segmentation,” NeuroImage, vol. 26, no. 3, pp. 839–851, 2005. View at Publisher · View at Google Scholar · View at Scopus