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Non-rigid Diffeomorphic Image Registration of Medical Images Using Polynomial Expansion

  • Daniel Forsberg
  • Mats Andersson
  • Hans Knutsson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

Abstract

The use of polynomial expansion in image registration has previously been shown to be beneficial due to fast convergence and high accuracy. However, earlier work has only briefly out-lined how non-rigid image registration is handled, e.g. not discussing issues like regularization of the displacement field or how to accumulate the displacement field. In this work, it is shown how non-rigid image registration based upon polynomial expansion can be integrated into a generic framework for non-rigid image registration achieving diffeomorphic displacement fields. The proposed non-rigid image registration algorithm using diffeomorphic field accumulation is evaluated on both synthetically deformed data and real image data and compared to additive field accumulation. The results clearly demonstrate the power of the diffeomorphic field accumulation.

Keywords

Image Registration Polynomial Expansion Registration Accuracy Additive Accumulation Harmonic Energy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Arsigny, V., Commowick, O., Pennec, X., Ayache, N.: A Log-Euclidean Framework for Statistics on Diffeomorphisms. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 924–931. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Ashburner, J.: A fast diffeomorphic image registration algorithm. NeuroImage 38(1), 95–113 (2007)CrossRefGoogle Scholar
  3. 3.
    Farnebäck, G.: Polynomial expansion for orientation and motion estimation. Ph.D. thesis, Linköping University, Sweden (2002)Google Scholar
  4. 4.
    Farnebäck, G., Westin, C.-F.: Affine and Deformable Registration Based on Polynomial Expansion. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 857–864. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  5. 5.
    Janssens, G., Jacques, L., de Xivry, J.O., Geets, X., Macq, B.: Diffeomorphic registration of images with variable contrast enhancement. International Journal of Biomedical Imaging (January 2011)Google Scholar
  6. 6.
    Knutsson, H., Westin, C.F.: Normalized and differential convolution: Methods for interpolation and filtering of incomplete and uncertain data. In: Proceedings of Computer Vision and Pattern Recognition 1993, New York City, USA, June16-19, pp. 515–523 (1993)Google Scholar
  7. 7.
    Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Non-parametric Diffeomorphic Image Registration with the Demons Algorithm. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 319–326. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Wang, Y.J., Farnebck, G., Westin, C.F.: Multi-affine registration using local polynomial expansion. Journal of Zhejiang University - Science C 11, 495–503 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Daniel Forsberg
    • 1
    • 2
    • 3
  • Mats Andersson
    • 1
    • 2
  • Hans Knutsson
    • 1
    • 2
  1. 1.Department of Biomedical EngineeringLinköping UniversitySweden
  2. 2.Center for Medical Image Science and VisualizationLinköping UniversitySweden
  3. 3.Sectra ImtecLinköpingSweden

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