A global optimization method based on mutual information is proposed for multimodality medical image registration. First external surfaces are extracted from various image modalities and the ICP algorithm is adopted to initially align unregistered images. Then the registration is performed by maximization of normalized mutual information using a deterministic global optimization algorithm named Dividing Rectangles. The surface based matching is used to provide a good start point for Dividing Rectangles in order to fully utilize its high efficiency in small search space. The results of experiment on three dimensional human brain data show that this method is accurate

fast

and avoids local minimums efficiently.