Abstract
B-spline based free-form deformation (FFD) is a widely used technique in nonrigid image registration. In general, a third-order B-spline function is used, because of its favorable trade-off between smoothness and computational cost. Compared with the third-order B-splines, a B-spline function with a lower order has shorter support length, which means it is computationally more attractive. However, a lower-order function is seldom used to construct the deformation field for registration since it is less smooth. In this work, we propose a randomly perturbed FFD strategy (RPFFD) which uses a lower-order B-spline FFD with a random perturbation around the original position to approximate a higher-order B-spline FFD in a stochastic fashion. For a given D-dimensional nth-order FFD, its corresponding (nāāā1)th-order RPFFD has \((\frac{n}{n+1})^{D}\) times lower computational complexity. Experiments on 3D lung and brain data show that, with this lower computational complexity, the proposed RPFFD registration results in even slightly better accuracy and smoothness than the traditional higher-order FFD.
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References
Rueckert, D., Sonoda, L.I., Hayes, C., et al.: Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Transactions on Medical ImagingĀ 18(8), 712ā721 (1999)
De Boor, C.: A practical guide to splines, vol.Ā 27. Springer, New York (1978)
Maintz, J., Viergever, M.A.: A survey of medical image registration. Medical Image AnalysisĀ 2(1), 1ā36 (1998)
Nocedal, J., Wright, S.J.: Numerical optimization. Springer, New York (1999)
Klein, S., Staring, M., Pluim, J.P.W.: Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines. IEEE Transactions on Image ProcessingĀ 16(12), 2879ā2890 (2007)
Klein, S., Pluim, J.P.W., Staring, M., Viergever, M.A.: Adaptive stochastic gradient descent optimisation for image registration. International Journal of Computer VisionĀ 81(3), 227ā239 (2009)
Unser, M., Aldroubi, A., Eden, M.: Fast B-spline transforms for continuous image representation and interpolation. IEEE Transactions on Pattern Analysis and Machine IntelligenceĀ 13(3), 277ā285 (1991)
Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.P.W.: Elastix: a toolbox for intensity-based medical image registration. IEEE Transactions on Medical ImagingĀ 29(1), 196ā205 (2010)
Tustison, N.J., Avants, B.B., Gee, J.C.: Directly manipulated free-form deformation image registration. IEEE Transactions on Image ProcessingĀ 18(3), 624ā635 (2009)
Maryak, J.L., Chin, D.C.: Global random optimization by simultaneous perturbation stochastic approximation. In: Proceedings of the American Control Conference, vol.Ā 2, pp. 756ā762. IEEE (2001)
Sun, W., Niessen, W.J., van Stralen, M., Klein, S.: Simultaneous multiresolution strategies for nonrigid image registration. IEEE Transactions on Image ProcessingĀ 22(12), 4905ā4917 (2013)
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Sun, W., Niessen, W.J., Klein, S. (2014). Randomly Perturbed Free-Form Deformation for Nonrigid Image Registration. In: Ourselin, S., Modat, M. (eds) Biomedical Image Registration. WBIR 2014. Lecture Notes in Computer Science, vol 8545. Springer, Cham. https://doi.org/10.1007/978-3-319-08554-8_7
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DOI: https://doi.org/10.1007/978-3-319-08554-8_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08553-1
Online ISBN: 978-3-319-08554-8
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