This project focuses on medical image fusion using multi-modal brain MRI scans (T1ce, T2, FLAIR) from the BraTS2020 dataset. I built a full pipeline for preprocessing, fusion (PCA, Wavelet Transform, Laplacian Pyramid), and evaluation (SSIM, PSNR, Entropy, Mutual Information). The best-performing method (Sym4 wavelet + Max Rule) achieved SSIM: 0.82 and PSNR: 25.27 dB. Tools Used: Python, NumPy, MONAI, PyWavelets, Nibabel, Matplotlib, Scikit-Image Contribution: Image normalization and spatial preprocessing Multiple fusion strategies (Weighted Avg, PCA, Wavelet) Quality evaluation and visualization Exported results for 150 patients Ready-to-use metrics for research or diagnostic use Outcome: Produced clear, information-rich MRI images to assist doctors and researchers in brain tumor diagnosis.