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Medical image fusion has been used to derive the useful information from multi modal medical images. The proposed methodology introduces evolutionary approaches for robust and automatic extraction of information from different modality images. This evolutionary fusion strategy implements multiresolution decomposition of the input images using wavelet transform. It is because, the analysis of input images at multiple resolutions able to extracts more fine details and improves the quality of the composite fused image. The proposed approach is also independent of any manual marking or knowledge of fiducial points and starts the fusion procedure automatically. The performance of the genetic based evolutionary algorithm is compared with fuzzy based fusion technique using mutual information as the similarity measuring metric. Experimental results show that genetic searching based fusion technique improves the quality of the fused images significantly over the fuzzy approaches.