Utilizing model-based clustering (unsupervised) for functional magnetic resonance imaging (fMRI) data. The developed methods (Chen and Maitra (2018, manuscript)) include 2D and 3D clustering analyses (for p-values with voxel locations) and segmentation analyses (for p-values alone) for fMRI data where p-values indicate significant level of activation responding to stimulate of interesting. The analyses are mainly identifying active voxel/signal associated with normal brain behaviors. Analysis pipelines (R scripts) utilizing this package (see examples in 'inst/workflow/') is also implemented with high performance techniques.
Version: | 0.1-0 |
Depends: | R (≥ 3.4.0) |
Imports: | MASS, Matrix, RColorBrewer, fftw, MixSim, EMCluster |
Enhances: | pbdMPI (≥ 0.3-4), AnalyzeFMRI, oro.nifti |
Published: | 2018-04-26 |
Author: | Wei-Chen Chen [aut, cre], Ranjan Maitra [aut], Dan Nettleton [ctb] |
Maintainer: | Wei-Chen Chen <wccsnow at gmail.com> |
BugReports: | https://github.com/snoweye/MixfMRI/issues |
License: | Mozilla Public License 2.0 |
URL: | https://github.com/snoweye/MixfMRI |
NeedsCompilation: | yes |
Citation: | MixfMRI citation info |
Materials: | README ChangeLog INSTALL |
CRAN checks: | MixfMRI results |
Reference manual: | MixfMRI.pdf |
Vignettes: |
MixfMRI-guide |
Package source: | MixfMRI_0.1-0.tar.gz |
Windows binaries: | r-devel: MixfMRI_0.1-0.zip, r-release: MixfMRI_0.1-0.zip, r-oldrel: MixfMRI_0.1-0.zip |
macOS binaries: | r-release: MixfMRI_0.1-0.tgz, r-oldrel: MixfMRI_0.1-0.tgz |
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