Fusion of CT and MRI Images Based on Fuzzy Logic and Discrete Wavelet Transform

Abstract — Medical image fusion is used to integrate the essential features present in different medical images into a single image to improve the clinical accuracy to take better decisions. Multimodal medical image fusion combines the images obtained from different modalities like Positron Emission Tomography (PET), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and others. CT scan provides detailed information on bony structures whereas MRI scan provides details on soft tissues. Fusion of these images is useful for doctors to diagnose and plan treatment for patients. In this paper, an image fusion methodology for fusing CT and MRI using fuzzy logic is presented. The bone tissue from CT image and the soft tissue from MRI image is segmented using Otsu’s segmentation method. They are then fused using Fuzzy Logic and Discrete Wavelet Transforms. Experiments are conducted for both Mamdani type Fuzzy Logic System (FLS) and Sugeno type FLS with varying number of membership functions. The results are analyzed using various performance metrics. Sugeno FLS has produced better results compared to Mamdani FLS