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Graphical-Model-based Multivariate Analysis (GAMMA) is a Bayesian data mining software for structural and functional magnetic-resonance data. GAMMA can be applied for the cross-sectional or longitudinal study of morphometric difference in structure MR data, and the activation pattern detection in fMRI. From the machine learning point of view, GAMMA can be used for either unsupervised or supervised learning.
GAMMA is available as freeware under the GPL. Source code is available. Please send comments and bug reports to rong.chen@uphs.upenn.edu
Reference:
[1] Chen, R., Herskovits, E. H.: A Bayesian Network Classifier with Inverse Tree Structure for Voxel-wise MR Image Analysis. Proceedings of the eleventh conference of SIGKDD Page: 4-12, August 2005.
[2] Chen, R., Herskovits, E. H. : Graphical-Model-based Morphometric Analysis. IEEE Transaction on medical imaging Vol. 24: 1237-1248, October 2005.
[3] Chen, R., Herskovits, E. H.: Graphical-model-based Multivariate Analysis of Functional Magnetic Resonance Data. NeuroImage, 635-647 2007.