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Computer aided fusion of multi modality medical images provides a very promising diagnostic tool with numerous clinical applications. The objective of this paper is to present a novel scheme of medical imaging fusion. We define “local to be fused” of the process of image fusion as a generalized local, which extends airspace locals to generalized locals, and promotes the airspace local priority to generalized local priority. Based on this priority, the volume-weighted of token coefficient of images is introduced and weighted so that multi-modal medical image fusion is achieved with high quality. This scheme is applied to CT/MRI datasets and results show the effectiveness of the method.