A Brief Analysis of Multimodal Medical Image Fusion Techniques

Recently, image fusion has become one of the most promising fields in processing since it plays an essential role different applications, such as medical diagnosis and clarification images. Multimodal Medical Image Fusion (MMIF) enhances quality images by combining two or more from modalities to obtain improved fused that is clearer than original ones. Choosing best MMIF technique which produces important problems assessment techniques. In this paper, a complete survey on techniques presented, along with imaging modalities, steps levels, methodology MMIF. There are several Computed Tomography (CT), Positron Emission (PET), Magnetic Resonance Imaging (MRI), Single Photon (SPECT). categorized into six main categories: spatial domain, transform fusion, fuzzy logic, morphological methods, sparse representation methods. The levels pixel-level, feature-level, decision-level. evaluation metrics can be subjective/qualitative objective/quantitative Furthermore, detailed comparison between obtained results for significant also presented highlight pros cons each technique.