Global registration of multiple point sets: feasibility and applications in multi-fragment fracture fixation

Authors:
Mehdi Hedjazi Moghari;Purang Abolmaesumi
Affiliations:
Department of Electrical and Computer Engineering, Queen's University, Canada;Department of Electrical and Computer Engineering, Queen's University, Canada and School of Computing, Queen's University, Canada
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Year:
2007

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Abstract

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.