Authors : D. Sheefa Ruby Grace and Mary Immaculate Sheela
Abstract: Image fusion is a process of obtaining a single image by combining multiple images. Since, the source images are obtained from various detectors at dissimilar times, some information will be missing in one source image and that missing information may present in another source image. Hence, the physicians are in the need of combining the fine information from both source images into a single one. The objective of image fusion is providing utmost information that are missing in the source images. In this study CT (Computed Tomography) and PET (Positron Emission Tomography) images are get fused. The CT imaging provides anatomic information whereas the PET image provides functional information of the body. The proposed method fused the images using contourlet based random block selection method with MAX fusion rule. It is proved that the proposed method provides better result with less number of computations. Experimental results are taken by writing MATLAB code. To prove the quality of fused image, performance measures such as Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Mutual Information (MI) are used.
D. Sheefa Ruby Grace and Mary Immaculate Sheela, 2020. Medical Image Fusion of Multi Modal Images using Random Block Selection Method. International Journal of Soft Computing, 15: 30-33.