(untitled) (International Journal of Engineering and Computer Science, 2014)
now a day, multimodality medical image fusion has drawn lots of attention with the increasing rate at which multimodality medical images are available in many clinic application fields. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. CT scans and MRI scans contains details regarding soft and hard tissues. For medical diagnosis, CT provides the better information on denser tissue with less distortion, while MRI offers better information on soft tissue with more distortion. In this paper, a fusion method is proposed for multimodal medical images based on Discrete Wavelet Transform Directive contrast fusion rule is used in this method. The source medical images are first transformed by DWT followed by combining low- and high-frequency components. Now to reconstruct fused image Inverse Discrete wavelet transform is performed. Experimental results and comparative study show that the proposed fusion framework provides an effective way to enable more accurate analysis of multimodality images.