Image fusion is the process of extracting meaningful information from two or more images and integrating them to form one fused image. Image fusion is important within many different image processing fields from remote sensing to medical applications. The fusion of medical images taken at the same slice/part of the body by different modalities is very useful technique in medical diagnosis. Medical image fusions tried with wavelet transform methods proved to be image dependent and preservation of high frequency contents of the image. In this study, we tried with all possible transform is applied for fusion for 2D. The edges, singularities and other high frequency contents of the fused image are well represented by the curvelet transform. The curvlet based fused result is better by visual appearance and quantitative analysis than their wavelet equivalents tried with the same fusion rules.