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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 726712, 6 pages
Research Article

A Novel Blind Separation Method in Magnetic Resonance Images

1School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China
2Key Laboratory of Integrated Electronic System, Ministry of Education, Chengdu 611731, China
3Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu 610072, China
4School of Computer Science & Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
5Southwest China Research Institute of Electronic Equipment, Chengdu 610036, China

Received 22 November 2013; Accepted 17 January 2014; Published 23 February 2014

Academic Editor: Yuanjie Zheng

Copyright © 2014 Jianbin Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A novel global search algorithm based method is proposed to separate MR images blindly in this paper. The key point of the method is the formulation of the new matrix which forms a generalized permutation of the original mixing matrix. Since the lowest entropy is closely associated with the smooth degree of source images, blind image separation can be formulated to an entropy minimization problem by using the property that most of neighbor pixels are smooth. A new dataset can be obtained by multiplying the mixed matrix by the inverse of the new matrix. Thus, the search technique is used to searching for the lowest entropy values of the new data. Accordingly, the separation weight vector associated with the lowest entropy values can be obtained. Compared with the conventional independent component analysis (ICA), the original signals in the proposed algorithm are not required to be independent. Simulation results on MR images are employed to further show the advantages of the proposed method.