A novel multi-modal medical image fusion method based on shift-invariant shearlet transform

Abstract

Medical image fusion plays an important role in clinical applications, such as image-guided surgery, image-guided radiotherapy, non-invasive diagnosis and treatment planning. Shearlet is a novel multi-scale geometric analysis (MGA) tool proposed recently. In order to overcome the drawback of the shearlet-based fusion methods that the pseudo-Gibbs phenomenon is easily caused around the singularities of the fused image, a new multi-modal medical image fusion method is proposed in shift-invariant shearlet transform domain. First, the original images are decomposed into lowpass sub-bands and highpass sub-bands; then, the lowpass sub-bands and high sub-bands are combined according to the fusion rules, respectively. All the operations are performed in shift-invariant shearlet domain. The final fused image is obtained by directly applying inverse shift-invariant shearlet transform to the fused lowpass sub-bands and highpass sub-bands. Experimental results demonstrate that the proposed method can not only suppress the pseudo-Gibbs phenomenon efficiently, but perform better than the popular wavelet transform-based method, contourlet transform-based method and non-subsampled contourlet transform-based method.

Keywords:

• medical image
• image fusion
• shearlet
• shift-invariance
• discrete shearlet transform

The authors would like to thank Professor W.-Q. Lim, one of the authorities on shearlet in University of Osnabrück. He gave us some helpful information and suggestions about the study of shearlet transform and the programs. The authors would also like to thank the anonymous reviewers for their helpful comments and advice which contributed much to the improvement of this paper.

This work is supported by the China Postdoctoral Science Foundation-funded project (no. 20090450866), Cooperation Project of Industry, Education and Academy, sponsored by Guangdong Province Government and Education Department of Chinese Government (no. 2009B090300057), the Fundamental Research Funds for the Central Universities, South China University of Technology (no. 2009ZM0077) and Science and Technology Key Project (no. 2009-Z-108-1) of Panyu District, Guangzhou City.