• DocumentCode
    1576023
  • Title

    Complexity Analysis of fMRI Time Sequences

  • Author

    Zhenghui Hu ; Pengcheng Shi

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • fYear
    2006
  • Firstpage
    2861
  • Lastpage
    2864
  • Abstract
    In this paper, we propose a novel strategy to explore population complexity and regularity from functional magnetic resonance imaging (fMRI) time series. The analysis is based on the sample entropy (SampEn), which performs a unbiased assessment of the complexity and regularity of time series dynamics. A fMRI scanning series from a healthy subject in resting state was analyzed to prove the effectiveness of this method. Moreover, the framework also includes a similarity test for particular populations. It can be considered as a valuable complementary method to classical fMRI analysis, and it could improve the understanding of complexity human brain functions.
  • Keywords
    biomedical MRI; brain; computational complexity; image sequences; medical image processing; neurophysiology; time series; complexity analysis; fMRI analysis; fMRI scanning series; fMRI time sequences; functional magnetic resonance imaging time series; human brain functions; regularity; sample entropy; similarity test; unbiased assessment; Entropy; Hemodynamics; Image analysis; Independent component analysis; Laboratories; Magnetic analysis; Magnetic resonance imaging; Statistics; Time measurement; Time series analysis; Complexity; Sample Entropy; fMRI;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.313026
  • Filename
    4107166