MRI-PET medical image fusion technique by combining contourlet and wavelet transform

Abstract

This paper proposes the application of the hybrid Multiscale transform in medical image fusion. The multimodality medical image fusion plays an important role in clinical applications which can support more accurate information for physicians to diagnosis diseases. In this paper, a new fusion scheme for Magnetic Resonance Images (MRI) and Positron Emission Tomography (PET) images based on hybrid transforms is proposed. PET/MRI medical image fusion has important clinical significance. Medical image fusion is the important step after registration, which is an integrative display method of two images. The PET image indicates the brain function and a low spatial resolution; MRI image shows the brain tissue anatomy and contains no functional information. Hence, a perfect fused image should contains both more functional information and more spatial characteristics with no spatial and color distortion. Firstly, the image is decomposed into high and low frequency subband coefficients with discrete wavelet transform (DWT). On these coefficients apply contourlet transform individually before going for fusion process. Later the fusion process is performed on contourlet components for each subband, for fusion the spatial frequency method is used. Finally, the proposed algorithm results are compared with different Multiscale transform techniques. According to simulation results, the algorithm holds useful information from source images. © 2013 Springer Science+Business Media New York.