Medical image fusion involves combination of multimodal sensor images to obtain both anatomical and functional data to be used by radiologists for the purpose of disease diagnosis, monitoring and research. This paper provides a comparative analysis of multiple fusion techniques that can be used to obtain accurate information from the intermodal MRI T1-T2 images. The source images are initially decomposed using stationary wavelet transform (SWT) and the approximations are reconstructed by discrete curvelet transform (DCT), the SWT and DCT are good for point and line discontinuities. The decomposed MRI approximation and detail components are fused using the different fusion rules. The reconstructed fused image is used to accurate identification of brain diseases such as 95.7% of brain lesion, 97.3% of Alzheimer’s disease and 98% of brain tumour. Various performance parameters are evaluated to compare the fusion techniques and the proposed method which provides better result is analysed. Copyright © 2020 Inderscience Enterprises Ltd.