Multimodal medical image fusion is an important task for the retrievalof complementary information from medical images. In this chapter,a novel framework for multimodal medical image fusion is proposed,which enables the decomposition of input images into low- and high frequencybands using framelet transform and utilizes local visibility andsmallest univalue segment assimilating nucleus (SUSAN) features fusionrules for coefficient selection at different levels. The final fused image isobtained from the superposition of selected coefficients in bot low- andhigh-frequency bands. The fused medical image that is produced by thisframework presents a visually better representation than the input images.Experimental results highlights the expediency and suitability of the proposedalgorithm and the efficiency is carried by the comparison madebetween proposed and existing algorithm. © 2015 by Nova Science Publishers, Inc. All rights reserved.