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Free-Form Deformation Using Lower-Order B-spline for Nonrigid Image Registration

  • Wei Sun
  • Wiro J. Niessen
  • Stefan Klein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

Abstract

In traditional free-form deformation (FFD) based registration, a B-spline basis function is commonly utilized to build the transformation model. As the B-spline order increases, the corresponding B-spline function becomes smoother. However, the higher-order B-spline has a larger support region, which means higher computational cost. For a given D-dimensional nth-order B-spline, an mth-order B-spline where (m ≤ n) has \((\frac{m+1}{n+1})^{D}\) times lower computational complexity. Generally, the third-order B-spline is regarded as keeping a good balance between smoothness and computation time. A lower-order function is seldom used to construct the deformation field for registration since it is less smooth. In this research, we investigated whether lower-order B-spline functions can be utilized for efficient registration, by using a novel stochastic perturbation technique in combination with a postponed smoothing technique to higher B-spline order. Experiments were performed with 3D lung and brain scans, demonstrating that the lower-order B-spline FFD in combination with the proposed perturbation and postponed smoothing techniques even results in better accuracy and smoothness than the traditional third-order B-spline registration, while substantially reducing computational costs.

Keywords

Registration Method Nonrigid Registration Registration Accuracy Stochastic Gradient Descent Target Registration Error 
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.

References

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wei Sun
    • 1
  • Wiro J. Niessen
    • 1
    • 2
  • Stefan Klein
    • 1
  1. 1.Biomedical Imaging Group RotterdamErasmus MCRotterdamThe Netherlands
  2. 2.Department of Image Science and Technology, Faculty of Applied SciencesDelft University of TechnologyDelftThe Netherlands

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