The process of achieving single fused image by combining relevant information from more images is image fusion. The resultant image will have more information when compared to the given input images. Image fusion has become a regulation for huge number of applications to derive the formal solutions in many fields like Aerial and Satellite imaging, Medical imaging, Robotic vision, Multi-focus image fusion, Digital camera application etc. Medical image fusion is very much essential for diagnosing diseases efficiently using multidimensional, multi-parameter image types. The objective of this paper is to design a multi modality medical image fusion system using different fusion methods with quantitative analysis. In this system, initially, images having different modalities can be considered as input such as CT (anatomical information) and MRI (functional information). Then the fusion methods viz., Contourlet Transform method, fusion tool methods (Average, Contrast Pyramid, Discrete Wavelet Transform (DWT), Filter-Subtraction-Decimate Pyramid (FSD), Gradient Pyramid, Laplacian Pyramid, Maximum, Minimum, Morphological Pyramid, Principal Component Analysis (PCA), Ratio Pyramid, and Shift Invariant Discrete Wavelet Transform Pyramid (SIDWT)) are applied and further resultant image is analyzed using various quantitative metrics such as Standard Deviation (SD), Entropy (EN), and Power Signal to Noise Ratio (PSNR) for performance evaluation. From the experimental results, it is observed that the Contourlet Transform method perform well than the fusion tool methods are proved through all metrics. © 2016, International Journal of Pharmacy and Technology. All rights reserved.