An overlap invariant entropy measure of 3D medical image alignment

This paper is concerned with the development of entropy-based registration criteria for automated 3D multi-modality medical image alignment. In this a pplication where misalignment can be large with respect to the imaged field of view, invariance to overlap statistics is an important consideration. C urrent entropy measures are reviewed and a normalised measure is proposed w hich is simply the ratio of the sum of the marginal entropies and the joint entropy. The effect of changing overlap on current entropy measures and th is normalised measure are compared using a simple image model and experimen ts on clinical image data. Results indicate that the normalised entropy mea sure provides significantly improved behaviour over a range of imaged field s of view. (C) 1999 Pattern Recognition Society. Published by Elsevier Scie nce Ltd. All rights reserved.