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.
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Keywords
- Registration Method
- Nonrigid Registration
- Registration Accuracy
- Stochastic Gradient Descent
- Target Registration Error
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References
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Sun, W., Niessen, W.J., Klein, S. (2014). Free-Form Deformation Using Lower-Order B-spline for Nonrigid Image Registration. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_25
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DOI: https://doi.org/10.1007/978-3-319-10404-1_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10403-4
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