Efficient numerical schemes for gradient vector flow
Pattern Recognition
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Similarity measure plays a critical role in image registration. Mutual information (MI) has been proved to be a promising measure used widely in multi-modality image registration. However, mutual information only takes statistical information into consideration, while spatial information is not even considered. In this paper, a novel approach is proposed to incorporate spatial information into MI through gradient vector flow (GVF). Mutual information now is calculated from the GVF-intensity (GVFI) map of the original images instead of their intensity values. Multimodality brain image registration was performed to test the accuracy and robustness of the proposed method. Experimental results showed that the success rate of our method is higher than that of traditional MI-based registration.