MRI and PET image fusion using structure tensor and dual ripplet-II transform

Medical image fusion aims at preserving salient image features, reducing the redundancy, and increasing the interpretation quality of images in clinical applications e.g. image-guided surgery. The PET image exhibits functional characteristic with low spatial resolution, while the MRI image exhibits brain tissue anatomy with high spatial resolution. Therefore, the image fusion task is carried out to inject the structural and anatomical information of the high-resolution MRI image into the metabolic information of the PET image. This paper firstly introduces the dual ripplet-II transform (DRT) to overcome the shift variance problem caused by the ripplet-II transform. The proposed transform incorporates the dual-tree complex wavelet into the traditional ripplet-II transform. Secondly, the proposed method takes advantage of the structure tensor and DRT to effectively merge the MRI and PET images. To this end, an objective function is proposed which exploits a weighting matrix to preserve more color and spatial information. Visual and statistical analyses show that the proposed method improves the visual quality and increases the quantitative criteria based on mutual information, edge information, spatial frequency, and structural similarity.