Image Fusion with CT and MRI Images for Improving the Quality of Diagnostics

To create a single image with the most information possible, two photographs of same model are combined through the process of image fusion. Many image-processing applications, including satellite imaging, remote sensing, and picture fusion, are crucial. The study of fusing images has developed to support the development of the above applications, and it has since expanded to include research on medical imaging. The merger of magnetic resonance (MR) and computerized tomography (CT) images is accomplished by using a curvelet-based method, which is presented in this chapter. The goal of merging an MR image and a CT image of the same organ is to create a unique image that contains the most diagnostically useful information on that organ. Wavelet transform has been suggested in some attempts to fuse MR and CT images. Given the number of items and curved forms in medical photos and after fusion, the curvelet transform is expected to perform better than the wavelet transform. According to the simulation results, the curvelet transform outperforms the wavelet transform when merging MR and CT images, in terms of visual quality and peak signal-to-noise ratio (PSNR).