Fast and Accurate Data Extraction for Near Real-Time Registration of 3-D Ultrasound and Computed Tomography in Orthopedic Surgery

Abstract

Automatic, accurate and real-time registration is an important step in providing effective guidance and successful anatomic restoration in ultrasound (US)-based computer assisted orthopedic surgery. We propose a method in which local phase-based bone surfaces, extracted from intra-operative US data, are registered to pre-operatively segmented computed tomography data. Extracted bone surfaces are downsampled and reinforced with high curvature features. A novel hierarchical simplification algorithm is used to further optimize the point clouds. The final point clouds are represented as Gaussian mixture models and iteratively matched by minimizing the dissimilarity between them using an L2 metric. For 44 clinical data sets from 25 pelvic fracture patients and 49 phantom data sets, we report mean surface registration accuracies of 0.31 and 0.77 mm, respectively, with an average registration time of 1.41 s. Our results suggest the viability and potential of the chosen method for real-time intra-operative registration in orthopedic surgery.

Keywords: Barnes–Hut algorithm; Curvature; Gaussian mixture model registration; Local phase features; Particle simulation; Point cloud matching; Ultrasound–computed tomography registration.