Multi-step 3D/2D Image Registration for Image-guided Spinal Surgery

We presented a set of methods for registration of preoperative CT data set to intra-operative X-ray images in minimally invasive image-guided spinal surgery. The registration procedure is composed of two steps. Firstly, a rough registration using a variant form of Iterative Closest Point algorithm is adopted to get an overlapped area. Secondly, the fine registration is performed based on gradient projection features. In this step, we introduce a similarity measure of CT gradient projections and use genetic algorithm combined with Powell´s maximization method as optimization strategy, which is able to increase the precision of the registration. The successive registration rate achieves 92% and 81% respectively on simulation data and clinical phantom research. The experimental results show that proposed method is suitable for clinical application with good robustness.