Fusion of The Multimodal Medical Images To Enhance The Quality Using Discrete Wavelet Transform

Abstract

Abstract The operation of medical image fusion is to merge various images from different imaging modalities in to one image fused. The quality of image fused is improved especially decrease randomness, that’s done by extracting the useful information of multiple images in one image. To rise the diagnosis and estimate of many medical problems by using clinical application of medical images and improving the accuracy medical imaging clinical is the most important goal of multi_modal image fusion algorithms. There are many types of modality used as a reference in medical image fusion like X_ray, Ultrasound, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Computed Tomography (CT). In this work, a multi solution images are used and coming from (CT) and (MRI) by Discrete Wavelet Transform (DWT) techniques to get a high quality image fusion. It can be proved the improvement in performance of image quality after fusion techniques by using some popular parameters of image metrics to test the image as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM). The quality improve of the fused image by tested and analyzed as low MSE of 0.02632, higher PSNR of 15.7955 and higher SSIM of 0.75434.