Adopting Quaternion Wavelet Transform to Fuse Multi-Modal Medical Images

Journal of medical and biological engineering
Peng GengJianhua Liu

Abstract

Medical image fusion plays an important role in clinical applications such as image-guided surgery, image-guided radiotherapy, noninvasive diagnosis, and treatment planning. In this paper, we propose a novel multi-modal medical image fusion method based on simplified pulse-coupled neural network and quaternion wavelet transform. The proposed fusion algorithm is capable of combining not only pairs of computed tomography (CT) and magnetic resonance (MR) images, but also pairs of CT and proton-density-weighted MR images, and multi-spectral MR images such as T1 and T2. Experiments on six pairs of multi-modal medical images are conducted to compare the proposed scheme with four existing methods. The performances of various methods are investigated using mutual information metrics and comprehensive fusion performance characterization (total fusion performance, fusion loss, and modified fusion artifacts criteria). The experimental results show that the proposed algorithm not only extracts more important visual information from source images, but also effectively avoids introducing artificial information into fused medical images. It significantly outperforms existing medical image fusion methods in terms of subjective performance and ...Continue Reading

References

Jan 19, 2000·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·J KettenbachF A Jolesz
Sep 21, 2004·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Valdimir S Petrović, Costas S Xydeas
Jun 6, 2006·Computer Methods and Programs in Biomedicine·Yang-Ming Zhu, Steven M Cochoff
Jul 1, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Wai Lam ChanRichard G Baraniuk
Jul 25, 2012·Medical & Biological Engineering & Computing·Sudeb Das, Malay Kumar Kundu

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Citations

Jan 30, 2020·Medical & Biological Engineering & Computing·Satya Prakash Yadav, Sachin Yadav

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