On fiducial target registration error in the presence of anisotropic noise

Authors:
Burton Ma;Mehdi H. Moghari;Randy E. Ellis;Purang Abolmaesumi
Affiliations:
Human Mobility Research Centre, Kingston General Hospital, Kingston, Ontario, Canada;Department of Electrical Engineering, Queen's University, Kingston, Ontario, Canada;Human Mobility Research Centre, Kingston General Hospital, Kingston, Ontario, Canada and School of Computing, Queen's University, Kingston, Ontario, Canada;Human Mobility Research Centre, Kingston General Hospital, Kingston, Ontario, Canada and Department of Electrical Engineering, Queen's University, Kingston, Ontario, Canada and School of Computing ...
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Year:
2007

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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.