A new method for CT to fluoroscope registration based on unscented Kalman filter.
We propose a new method for CT to fluoroscope registration which is very robust and has a wide capture range. The method relies on the Unscented Kalman Filter to search for an optimal registration solution and on modern commodity graphics cards for fast generation of digitally reconstructed radiographs. We extensively test our method using three different anatomical data sets and compare it with an implementation of the commonly used simplex-based method. The experimental results firmly support that, under the same testing conditions, our proposed technique outperforms the simplex-based method in capture range while providing comparable accuracy and computation time.
Gong
Ren Hui
RH
School of Computing, Queen's University, Kingston, ON K7L 3N6, Canada.
Stewart
A James
AJ
Abolmaesumi
Purang
P
D000465:Algorithms; D001185:Artificial Intelligence; D005471:Fluoroscopy / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods*