Abstract
This paper presents a novel method for medical image signal fusion using complex-valued wavelets to enhance the information content in the fused signal from a perceptual manner. The proposed method introduces an adaptively weighted aggregation of signal characteristics based on the phase characteristics of medical image signals. The proposed method exploits the phase characteristics of the image signals to adaptively accentuate important anatomical and functional characteristics captured by each image signal during the signal fusion process. Experimental results show that the proposed method can improve the visualization of important anatomical and functional characteristics from different medical image signals in the fused image signal when compared with non-adaptive image signal fusion methods.
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