title: 3D ultrasound-CT registration in orthopaedic trauma using GMM registration with optimized particle simulation-based data reduction.
abstract: Accurate real-time registration of intra-operative ultrasound (US) to computed tomography (CT) remains a challenging problem. In orthopedic applications, a recent promising approach proposed the use of Gaussian mixture modeling for bone surface registration. Though relatively successful, the method relied on naive and error prone subsampling of the surfaces registered to reduce computational cost and also heavily relied on heuristically-set parameters for bone surface generation. In this paper, we present an improved approach employing a novel point simplification method that redistributes surface points to better represent the surface achieving near real-time registration with higher accuracy and robustness. We also present a framework for automating the parameter selection in the bone surface extraction step. For validation, we present extensive quantitative tests on phantom and clinical data obtained by scanning patients with pelvic ring fractures in the operating room. We show an 89% average improvement in target registration error over the recent GMM registration based method.
authors.affiliation: Departments of Orthopaedics, University of British Columbia, Vancouver, BC, Canada. ilker.hacihaliloglu@hiphealth.ca
authors.forename: Ilker
authors.initials: I
authors.lastname: Hacihaliloglu
authors.forename: Anna
authors.initials: A
authors.lastname: Brounstein
authors.forename: Pierre
authors.initials: P
authors.lastname: Guy
authors.forename: Antony
authors.initials: A
authors.lastname: Hodgson
authors.forename: Rafeef
authors.initials: R
authors.lastname: Abugharbieh
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D050723:Fractures, Bone / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods; D010384:Pelvic Bones / Q000000981:diagnostic imaging* / Q000293:injuries*; 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; D014463:Ultrasonography / Q000379:methods*