Abstract
The over-complete case remains a difficult problem in the field of independent component analysis (ICA). In this article we combine a technique called "region of interest" (ROI) with a standard complete ICA. We show how to create a mask using ICA, then using the masked data for a second ICA. At the same time this method eliminates a commonly necessary model-based step in fMRI data analysis. We also demonstrate our approach on a real world fMRI data set example. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Keck, I. R., Churan, J., Theis, F. J., Gruber, P., Lang, E. W., & Puntonet, C. G. (2006). Region of interest based independent component analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4232 LNCS, pp. 1048–1057). Springer Verlag. https://doi.org/10.1007/11893028_117
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