(untitled) (مجلة العلوم الشاملة, 2025)
Integration of supplemental data from several imaging methods depends critically on medical image fusion. Particularly aimed at brain tumor detection across four datasets, this study assesses and contrasts two wavelet based fusion techniques applied to fuse Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans: Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT). Additionally examined in the study is how different wavelet families affect fusion performance. Based on PSNR, RMSE, and entropy measures, experimental results show that SWT based fusion consistently outperforms DWT based fusion, with the bior2.2 wavelet family providing the best performance.