Data fusion technique is a powerful tool for extracting higher quality information from large amount of remote sensing images or various types of medical images and eliminating redundancy among these images. Traditional multi-resolution analysis image fusion methods always decompose multitemporal images into low and high frequency parts, then fuse the low frequency part of each image into one low frequency part and do not deal with fusion of high frequency parts which represent image' details, such as edges, corners and ridges. In this paper, the fusion of the CT image which gives the information about boundary of the affected area and MR image which gives the information about the tissues affected by diseases is considered and the resultant image provides all boundary and internal details for diagnostic purpose. Entropy based analysis is done on fused CT and MR images using lifting wavelet and double density dual tree DWT