Medical image fusion using discrete wavelet transform and lifting scheme

Multiple sclerosis (MS) is an inflammatory disease of central nervous system. Magnetic resonance (MR) images play an important role in diagnosis of MS because of the ability in detection of white matter lesions. Proper detection of lesions and their boundaries is crucial for diagnosis. T1 weighted images are the most preferred modal in diagnosis, but enriching them with information of other modals could increase accuracy of lesion detection and thus diagnosis. In this paper a new method based on lifting scheme is suggested to fuse modals of MR. in this algorithm, lifting wavelet transform is used to decompose source images into different subbands. Different fusion rules are applied to fuse subbands and achieve fused image. Numerical and visual analyses prove efficiency of propped method in gathering complemental information of source images in one image.