Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition

Multimodal medical image fusion, emerging as a hot topic, aims to fuse images with complementary multi-source information. In this paper, we propose a novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzzy logic technology. First, the SPD method is employed to extract two salient features for fusion discrimination. Next, two novel fusion decision maps called an incomplete fusion map and supplemental fusion map are constructed from salient features. In this step, the supplemental map is constructed by our defined two different fuzzy logic systems. The supplemental and incomplete maps are then combined to construct an initial fusion map. The final fusion map is obtained by processing the initial fusion map with a Gaussian filter. Finally, a weighted average approach is adopted to create the final fused image. Additionally, an effective color medical image fusion scheme that can effectively prevent color distortion and obtain superior diagnostic effects is also proposed to enhance fused images. Experimental results clearly demonstrate that the proposed method outperforms state-of-theart methods in terms of subjective visual and quantitative evaluations.