医学图像配准，医学图像2D_3D配准，基于vc++开发。-Abstract. We present a method that performs the rigid 2D/3D image registration

efficiently on the GPU. As one main contribution of this paper, we propose an

efficient method for generating realistic DRRs that are visually similar to X-ray

images. Therefore, we model some of the electronic post-processes of current X-

ray C-arm-systems. As another main contribution, the GPU is used to compute

eight intensity-based similarity measures between the DRR and the X-ray image

in parallel. A combination of these eight similarity measures is used as a new

similarity measure for the optimization. We evaluated the performance and the

precision of our 2D/3D image registration algorithm using two phantom models.

Compared to a CPU+GPU algorithm, which calculates the similarity measures

on the CPU, our GPU algorithm is between three and six times faster. In contrast

to single similarity measures, our new similarity measure achieved precise and

robust registration results for both phantom m