Abstract
We investigate the rigid registration of a set of points onto a surface for computer-guided oral implants surgery. We first formulate the Iterative Closest Point (ICP) algorithmas a Maximum Likelihood (ML) estimation of the transformation and the matches. Then, considering matches as a hidden random variable, we show that the ML estimation of the transformation alone leads to a criterion efficiently solved using an Expectation-Maximisation (EM) algorithm. The experimental section provides evidences that this new algorithmi s more robust and accurate than ICP and reaches a global accuracy of 0.2 mm with computation times compatible with a peroperative system.
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Granger, S., Pennec, X., Roche, A. (2001). Rigid Point-Surface Registration Using an EM Variant of ICP for Computer Guided Oral Implantology. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_90
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DOI: https://doi.org/10.1007/3-540-45468-3_90
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