fMRI data analysis using a novel clustering technique

This paper marks the beginning of a new way of analyzing fMRI images. The idea is to model these images with a mixture of Gaussians, that allows to carry out some complex tasks more easily. One application of this approach is the artifacts subtraction. It consists of removing certain high-intensity voxels that are not relevant to the analysis of the images. On the other hand, this approach provides a way to perform the feature extraction process that avoids the small sample size problem in classification tasks.

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