CT and MR Image Fusion Scheme in Nonsubsampled Contourlet Transform Domain

Abstract

Fusion of CT and MR images allows simultaneous visualization of details of bony anatomy provided by CT image and details of soft tissue anatomy provided by MR image. This helps the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. This paper aims at designing an effective CT and MR image fusion method. In the proposed method, first source images are decomposed by using nonsubsampled contourlet transform (NSCT) which is a shift-invariant, multiresolution and multidirection image decomposition transform. Maximum entropy of square of the coefficients with in a local window is used for low-frequency sub-band coefficient selection. Maximum weighted sum-modified Laplacian is used for high-frequency sub-bands coefficient selection. Finally fused image is obtained through inverse NSCT. CT and MR images of different cases have been used to test the proposed method and results are compared with those of the other conventional image fusion methods. Both visual analysis and quantitative evaluation of experimental results shows the superiority of proposed method as compared to other methods.