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
Link To Document :
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