Exploring the Intrinsic Structure of Magnetic Resonance Spectra Tumor Data Based on Independent Component Analysis and Correlation Analysis

  • Jian Ma
  • Zengqi Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


Analysis on magnetic resonance spectra (MRS) data gives a deep insight into pathology of many types of tumors. In this paper, a new method based on independent component analysis (ICA) and correlation analysis is proposed for MRS tumour data structure analysis. First, independent components and their coefficients are derived by ICA. Those components are interpreted in terms of metabolites, which interrelate with each other in tissues. Then correlation analysis is performed to reveal the interrelationship on coefficient of ICs, where residue dependence of components of metabolites remains. The method was performed on MRS data of hepatic encephalopathy. Experimental results reveal the intrinsic data structure and describe the pathological interrelation between parts of the structure successfully.


Hepatic Encephalopathy Independent Component Analysis Independent Component Analysis Intrinsic Structure Mutual Independence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jian Ma
    • 1
  • Zengqi Sun
    • 1
  1. 1.Department of Computer ScienceTsinghua UniversityBeijingChina

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