• DocumentCode
    3483578
  • Title

    Supervised map ICA: applications to brain functional MRI

  • Author

    Matsuyama, Yasuo ; Kawamura, Ryo

  • Author_Institution
    Dept. of Electr., Electron. & Comput. Eng., Waseda Univ., Tokyo, Japan
  • Volume
    5
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    2259
  • Abstract
    This paper gives a method to control or organize itself an activation pattern of fMRI maps obtained by ICA (independent component analysis). The presented method uses an additional term to the convex divergence´s gradient. The following merits are observed: (i) Prior knowledge can be effectively used so that obtained activation patterns properly reflect the task on the subject. (ii) Difficulty of finding the appropriate activation pattern due to the permutation can be avoided. Experiments on brain fMRI maps for visual cortices are tried and reported.
  • Keywords
    biomedical MRI; brain; independent component analysis; activation pattern; activation patterns; brain fMRI maps; brain functional MRI; convex divergence gradient; independent component analysis; prior knowledge; supervised map ICA; visual cortices; Application software; Continuous wavelet transforms; Convergence; Cost function; Independent component analysis; Iterative algorithms; Magnetic resonance imaging; Optimization methods; Signal analysis; Source separation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1201895
  • Filename
    1201895