Comparison of registered multimodal medical image fusion techniques

Abstract

Multimodal medical image fusion is an important task to retrieve an image which provides as much as information of the same organ at the same time it also helps to reduce the storage capacity to a single image. In this paper a comparison is done between existing image fusion techniques and the proposed multilevel fusion techniques. The proposed method fuses the coefficient based on maximum selection rule. Experiments have been done on three different sets of multimodal medical images of brain. The proposed method is visually and quantitatively compared with the existing methods. For the comparison of the proposed fusion method three different metrics is made used of, namely peak signal to noise ratio (PSNR), Entropy and Mutual Information. Comparison results show that the proposed fusion method works better than any of the existing fusion methods.