A New Algorithm for Multimodal Medical Image Fusion Based on the Surfacelet Transform

Nowadays, medical imaging becomes a common part of everyday clinical practices. Despite enormous progresses, still there is no single modality which can represent all aspects of the human body. For example, CT is suitable to view dense structures while MRI provides high resolution for soft tissue. In this paper, we propose a novel method for fusion of multimodal medical images. First, the surfacelet transform is used to decompose the source images. Then, we effectively combine the low and high frequency coefficients. Finally, inverse transform would provide the fused image. Experimental results exhibited the superior solution quality of our approach in comparison to a number of well-known counterpart algorithms.