Utilizing model-based clustering (unsupervised) for fMRI data especially in a distributed manner. The methods includes 2D and 3D clustering analyses and segmentation analyses for fMRI signals where p-values are significant levels of active voxels which respond to stimulate of interesting. The analyses are mainly identifying active voxels/signals from normal brain behaviors. Workflows are also implemented utilizing high performance techniques.
|License:||GPL (>= 2)|
The main function of this package is
fclust() that implements
model-based clustering algorithm for fMRI signal data and provides
unsupervised clustering results for the data. Several workflows implemented
with high-performance computing techniques are also built in for automatically
process clustering, hypothesis, cluster merging, and visualizations.
Wei-Chen Chen and Ranjan Maitra.
1 2 3 4
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.