Medical image fusion has been used to derive useful information from multimodality medical image data. The idea is to improve the image content by fusing images like computer tomography (CT) and magnetic resonance imaging (MRI) images, so as to provide more information to the doctor and clinical treatment planning system. This paper aims to demonstrate the application of wavelet transformation to multi-modality medical image fusion. This work covers the selection of wavelet function, the use of wavelet based fusion algorithms on medical image fusion of CT and MRI and the fusion image quality evaluation. We introduce the peak-to-peak signal-to-noise ratio (PSNR) method for measuring fusion effect. The performances of other two methods of image fusion based on pyramid-decomposition and simple image fusion attempts are briefly described for comparison. The experiment results demonstrate the effectiveness of the fusion scheme based on wavelet transform.
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