Global registration of multiple point sets: feasibility and applications in multi-fragment fracture fixation.
An algorithm to globally register multiple 3D data sets (point sets) within a general reference frame is proposed. The algorithm uses the Unscented Kalman Filter algorithm to simultaneously compute the registration transformations that map the data sets together, and to calculate the variances of the registration parameters. The data sets are either randomly generated, or collected from a set of fractured bone phantoms using Computed Tomography (CT) images. The algorithm robustly converges for isotropic Gaussian noise that could have perturbed the point coordinates in the data sets. It is also computationally efficient, and enables real-time global registration of multiple data sets, with applications in computer-assisted orthopaedic trauma surgery.
Moghari
Mehdi Hedjazi
MH
Department of Electrical and Computer Engineering, Queen's University, Canada.
Abolmaesumi
Purang
P
D000465:Algorithms; D001185:Artificial Intelligence; D005240:Feasibility Studies; D005264:Femoral Fractures / Q000000981:diagnostic imaging* / Q000601:surgery*; D005593:Fracture Fixation, Internal / Q000379:methods*; D006801:Humans; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016896:Treatment Outcome