Through merging the characteristics of several images from different modalities like magnetic resonance imaging (MRI), positron emission tomography (PET), and computed tomography (CT) into a single final image that contains the most significant information generated from all inputs, medical image fusion methods are widely utilized for assistance in medical diagnosis. In this work, a hybrid fusion technique for MRI and CT scans is proposed. The Discrete Cosine Transform (DCT) is used to separate the different frequency components, and Principal Component Analysis (PCA) is used to find the largest Eigen value of the covariance matrices for each image. of the input image, resulting in noise in the output images following the first two steps. When compared to known approaches, the efficacy assessment of CT-MRI image fusion using the hybrid technique Including Discrete Wavelet Transform (DWT) yields better image quality. All things considered, there is a good chance that the non-linear fusion rule will enhance picture fusion applications in the medical industry and other domains.