Towards real-time 3D US to CT bone image registration using phase and curvature feature based GMM matching

In order to use pre-operatively acquired computed tomography (CT) scans to guide surgical tool movements in orthopaedic surgery, the CT scan must first be registered to the patient's anatomy. Three-dimensional (3D) ultrasound (US) could potentially be used for this purpose if the registration process could be made sufficiently automatic, fast and accurate, but existing methods have difficulties meeting one or more of these criteria. We propose a near-real-time US-to-CT registration method that matches point clouds extracted from local phase images with points selected in part on the basis of local curvature. The point clouds are represented as Gaussian Mixture Models (GMM) and registration is achieved by minimizing the statistical dissimilarity between the GMMs using an L2 distance metric. We present quantitative and qualitative results on both phantom and clinical pelvis data and show a mean registration time of 2.11 s with a mean accuracy of 0.49 mm.