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Recently, maximization mutual information (MMI) of image intensities has been proposed as a new matching criterion for automated multimodality image registration. However, the success of the MMI relies on the similarity of the histogram distribution between the images to be fused. This condition is usually hard to be achieved in practical application. Besides, MMI is time consuming because it needs to find an optimal solution about six parameters (three for shifts and three for rotations) during the registration process. To overcome these drawbacks of using traditional MMI, a novel scheme, named improved MMI, which is based on fuzzy c-means (FCM) and MMI, is proposed. The experimental results, using MR and SPECT images, to confirm the superior performance of the proposed method in comparison with the traditional MMI method are also included.

IMPROVING MMI WITH ENHANCED-FCM FOR THE FUSION OF BRAIN MR AND SPECT IMAGES