Performance comparisons of multi-modal medical image registration algorithms

In this paper we study the performance of the maximization of mutual information (MMI) based registration algorithm using a select number of medical image data sets. Where appropriate, we present a comparison of the MMI based algorithm with surface based and centerline (medial axes) based registration algorithms. In the paper we first show that the MMI based registration algorithm can accurately estimate the registration parameters using real patient image data sets. We then present a data set where the MMI based estimates are not as accurate. For this image data set, the MMI based algorithm requires sufficiently close initialization to the true parameters. Also, we show that for such image data sets feature based algorithms, such as, surface based and the centerline based methods, can accurately estimate the registration parameters. The paper also discusses the effects of the optimization method (Powell´s versus Simplex) on the quality and computation time of the MMI based and correlation based registration algorithms.