Abstract

Abstract

Abstract. The registration of multimodal medical images is an important tool in surgical applications, since different scan modalities highlight complementary anatomical structures. We present a method of computing the best rigid registration of pairs of medical images of the same patient. The method uses prior information on the expected joint intensity distribution of the images when correctly aligned, given a priori registered training images. We discuss two methods of modeling the joint intensity distribution of the training data, mixture of Gaussians and Parzen windowing. The fitted Gaussians roughly correspond to various anatomical structures apparent in the images and provide a coarse anatomical segmentation of a registered image pair. Given a novel set of unregistered images, the algorithm computes the best registration by maximizing the log likelihood of the two images, given the transformation and the prior joint intensity model. Results aligning SPGR and dual-echo MR scans demonstrate that this algorithm is a fast registration method with a large region of convergence and sub-voxel registration accuracy.

No abstract

We describe an image-guided neurosurgery system which we have successfully used on 70 cases in the operating room. The system is designed to achieve high positional accuracy with a simple and efficient interface that interferes little with the operating room's usual procedures, but is general enough to use on a wide range of cases. It uses data from a laser scanner or a trackable probe to register segmented MR imagery to the patient's position in the operating room, and an optical tracking system to track head motion and localize medical instruments. Output visualizations for the surgeon consist of an "enhanced reality display," showing location of hidden internal structures, and an instrument tracking display, showing the location of instruments in the context of the MR imagery. Initial assessment of the system in the operating room indicates a high degree of robustness and accuracy.