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Image fusion plays a vital role for enhancing the quality of images in medical applications. It is known that CT images of brain shows the details of the bone structure and MRI images of brain shows the details of the soft tissue. The Objective of this research is to fuse CT (Computed Tomography) and MRI(Magnetic Resonance Imaging) of normal brain images and tumor affected brain images and to find out structural similarity(SSIM) of the fused image. Axial slice of normal brain and brain tumor images are taken for image fusion. Totally, 24 brain images has been taken out of which 6 pairs are normal brain images and another 6 pairs are tumor affected brain images. Techniques used are Graph-cut method for segmentation, Maximum method for fusion and Swarm Intelligence method for optimization. The proposed fusion method increases SSIM (Structural Similarity) when compared to conventional method of fusion. Tumor size in the fused image is also extracted and this fused image is helpful for doctors to analyse the post radio therapy patient or operated patient whether any tumor residues still exist. Also this method minimises the number of pixels and increases the information content in a single fused image. This technique aids the physician to analyse complementary details in a single image.
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