A global optimization strategy for 3D-2D registration of vascular images
K. K. Lau, Albert C. S. Chung · 2006
Although the presence of local minima is one of the major problems in high-dimensional image registration, only a few experimental works have been carried out to address this problem. In this study, a 3D-2D vascular image feature-based registration is done by producing Digital Reconstructed Radiographs (DRRs) of 3D images to match against the target 2D images. In addition, we propose a global optimization method based on the use of Powell's method at different resolution levels. To search the global minimum as effectively as possible, a large set of sample test points are systematically generated. The values of dissimilarity to the registered images in lower resolution environment are calculated. Powell's method is then applied to those test points with the lowest values for further minimization in the higher resolution. It is experimentally shown that our method can identify the global optimum in a normal clinical setting. The findings can have potential usage in the reconstruction of 3D models (e.g. guide wires) based on 2D medical visual information.