Affine Registration with Feature Space Mutual Information

This paper introduces two important issues of image registration. At first we want to recall the very general definition of mutual information that allows the choice of various feature spaces to perform image registration. Second we discuss the problem of finding the global maximum in an arbitrary feature space. We used a very general parallel, distributed memory, genetic optimization which turned out to be very robust. We restrict the examples to the context of multi-modal medical image registration but we want to point out that the approach is very general and therefore applicable to a wide range of other applications. The registration algorithm was analysed on a LINUX cluster.