科研之友
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摘要
Functional magnetic resonance imaging (fMRI) has emerged as a useful tool in the study of brain function, but the data process of fMRI is also unsolved. In this paper, proposed is a new hierarchical clustering analysis presented to localize brain function based on the idea of function group of human brain and a new spatial-temporal distance analysis., This method is that a Neighborhood correlation (NC) is utilized at first to get a primary imaging to choose the potential activation pixels and discard non-activation pixels to decrease the complexity of hierarchical algorithm. Then the new hierarchical clustering analysis is implemented to foci brain activation. The simulation test and the localization of brain activities in the vivo fMRI data show that it provides more accuracy and faster speed in detecting weak fMRI signals.
