A comparison of four algorithms for estimating 3-D rigid transformations
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
A Theoretical Comparison of Different Target Registration Error Estimators
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
On fiducial target registration error in the presence of anisotropic noise
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
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Rigid registration of pre-operative surgical plans to intra-operative coordinates of a patient is an important step in computer-assisted orthopaedic surgery. A good measure for registration accuracy is the target registration error (TRE) which is the distance after registration between a pair of corresponding points not used in the registration process. However, TRE is not a deterministic value, since there is always error in the localized features (points) utilized in the registration. In this situation, the distribution of TRE carries more information than TRE by itself. Previously, the distribution of TRE has been estimated with the accuracy of the first-order approximation. In this paper, we analytically approximate the TRE distribution up to at least the second-order accuracy based on the Unscented Kalman Filter algorithm.