Abstract
We present an extension of the symmetric ICP algorithm that is unbiased for an arbitrary number (N ≥ 2) of shapes, using rigid transformations and scaling. The method does not require the selection of a reference shape or registration order and hence it is unbiased towards any of the registered shapes. The functional to be minimized is non-linear in the transformation parameters and thus computationally complex. We therefore propose a first order approximation that estimates the transformation parameters in a closed form, with computational complexity \(\mathcal{O}(N^{2})\).
Using a set of wrist bones, we show that the least-squares minimization and the proposed approximation converge to the same solution. Experiments also show that the proposed algorithms lead to smaller registration errors than algorithms that select a reference shape or register to an evolving mean shape. The low computational cost and trivial parallelization enable the alignment of large numbers of bones.
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van de Giessen, M., Vos, F.M., Grimbergen, C.A., van Vliet, L.J., Streekstra, G.J. (2012). Groupwise Rigid Registration of Wrist Bones. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_20
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DOI: https://doi.org/10.1007/978-3-642-33418-4_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33417-7
Online ISBN: 978-3-642-33418-4
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