Effective image fusion method to study Alzheimer's disease using MR, PET images

In this paper we have proposed an effective fusion method to combine the information of brain MRI and PET images to study Alzheimer's disease of the patients. The proposed methodology is applied to the wavelet based multi-scale image fusion algorithm. In this method principal component analysis (PCA) approach for integrating each RGB component of approximation images decomposed by multiresolution analysis provides superior visual interpretation and high-quality synthesis of MRI and PET images. The proposed rule overcomes the instability and inconsistency of information occurring in the wavelet based decomposition of images. The experimental results show that this method is very much suitable for multimodal images, especially for integrating structural and functional information of brain MRI and PET data.