We have developed a novel similarity measure to evaluate image correspondence. Our method is based on the mutual information between images. The main difference to other mutual information approaches is that we incorporate spatial information using grey-level cooccurrence matrices, leading to a more general measurement. We have used this technique to evaluate two registration algorithms (local affine transformation and thin plate splines) applied to a dataset of mammographic images.