2D-3D registration is one of the underpinning technologies that enables image-guided intervention in computer-assisted orthopaedic surgery (CAOS). Preoperative 3D images and surgical plans need to be mapped to the patient in the operating room before they can be used to augment the surgical intervention, and this task is generally fulfilled by using 2D-3D registration which spatially aligns a preoperative 3D image to a set of intraoperative fluoroscopic images. The key problem in 2D-3D registration is to define an accurate similarity metric between the 2D and 3D data, and choose an appropriate optimization algorithm. Various similarity metrics and optimization algorithms have been proposed for 2D-3D registration; however, current techniques have several critical limitations. First, a good initial guess - usually within a few millimetres from the true solution - is required, and such capture range is often not wide enough for clinical use. Second, for currently used optimization algorithms, it is difficult to achieve a good balance between the computation efficiency and registration accuracy. Third, most current techniques register a 3D image of a single bone to a set of fluoroscopic images, but in many CAOS procedures, such as a multi-fragment fracture treatment, multiple bone pieces are involved. In this thesis, research has been conducted to investigate the above problems: 1) two new registration techniques are proposed that use recently developed optimization techniques, i.e. Unscented Kalman Filter (UKF) and Covariance Matrix Adaptation Evolution Strategy (CMA-ES), to improve the capture range for the 2D-3D registration problem; 2) a multiple-object 2D-3D registration technique is proposed that simultaneously aligns multiple 3D images of fracture fragments to a set of fluoroscopic images of fracture ensemble; 3) a new method is developed for fast and efficient construction of anatomical atlases; and 4) a new atlas-based multiple-object 2D-3D registration technique is proposed to aid fracture reduction in the absence of preoperative 3D images. Experimental results showed that: 1) by using the new optimization algorithms, the robustness against noise and outliers was improved, and the registrations could be performed more efficiently; 2) the simultaneous registration of multiple bone fragments could achieve a clinically acceptable global alignment among all objects with reasonable computation cost; and 3) the new atlas construction method could construct and update intensity atlases accurately and efficiently; and 4) the use of atlas in multiple-object 2D-3D registration is feasible. / Thesis (Ph.D, Computing) -- Queen's University, 2011-09-28 10:58:04.406