Utilizing model-based clustering (unsupervised)
for functional magnetic resonance imaging (fMRI) data.
The developed methods (Chen and Maitra (2023) <doi:10.1002/hbm.26425>)
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: |
0.1-3 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
MASS, Matrix, RColorBrewer, fftw, MixSim, EMCluster |
| Enhances: |
pbdMPI (≥ 0.3-4), oro.nifti |
| Published: |
2023-09-04 |
| DOI: |
10.32614/CRAN.package.MixfMRI |
| Author: |
Wei-Chen Chen [aut, cre],
Ranjan Maitra [aut],
Dan Nettleton [aut, ctb],
Pierre Lafaye De Micheaux [aut, ctb] (Threshold functions from
AnalyzeFMRI),
Jonathan L Marchini [aut, ctb] (Threshold functions from AnalyzeFMRI) |
| 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 [issues need fixing before 2024-10-21] |