An algorithm to globally register multiple 3D data sets (point sets) within a general reference frame is proposed. The algorithm uses the Unscented Kalman Filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of the registration parameters, The data sets are either randomly generated, or collected from a set of fractured bone phantoms using Computed Tomography (CT) images. The algorithm robustly converges for isotropic Gaussian noise that could have perturbed the point coordinates in the data sets. It is also computationally efficient, and enables real-time global registration of multiple data sets, with applications in computer-assisted orthopaedic trauma surgery. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Moghari, M. H., & Abolmaesumi, P. (2007). Global registration of multiple point sets: Feasibility and applications in multi-fragment fracture fixation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4792 LNCS, pp. 943–950). https://doi.org/10.1007/978-3-540-75759-7_114
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