Abstract
We study the effect of anisotropic noise on target registration error (TRE) by using a tracked and calibrated stylus tip as the fiducial registration application. We present a simple, efficient unscented Kalman filter algorithm that is suitable for fiducial registration even with a small number of fiducials. We also derive an equation that predicts TRE under anisotropic noise. The predicted TRE values are shown to closely match the simulated TRE values achieved using our UKF-based algorithm. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Ma, B., Moghari, M. H., Ellis, R. E., & Abolmaesumi, P. (2007). On fiducial target registration error in the presence of anisotropic noise. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4792 LNCS, pp. 628–635). Springer Verlag. https://doi.org/10.1007/978-3-540-75759-7_76
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