On fiducial target registration error in the presence of anisotropic noise.
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.
Human Mobility Research Centre, Kingston General Hospital, Kingston, Ontario, Canada. mab@cs.queensu.ca
Burton
B
Ma
Mehdi H
MH
Moghari
Randy E
RE
Ellis
Purang
P
Abolmaesumi
D000465:Algorithms; D016880:Anisotropy; D016477:Artifacts; D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique