RMINC

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A library for statistical analysis of neuroimaging data, focused on the MINC file format. Supports getting and writing volumes, running voxel-wise linear models, correlations, correcting for multiple comparisons with False Discovery Rate control, and more. With contributions from Jason Lerch, Chris Hammill, Jim Nikelski, Matthijs van Eede, Daniel Cassel, Yohan Yee, Gabe Devenyi, and Darren Fernandes.

Installation:

RMINC provides functionality for working with Medical Imaging NetCDF files, and relies on C libraries specifically designed for working with these files. For the richest experience please install the minc-toolkit (v2), either from the binary installer: http://bic-mni.github.io/ or from source: https://github.com/BIC-MNI/minc-toolkit-v2. If the toolkit is not found on your system, RMINC will attempt to install libminc from source. This requires a version of CMake greater than 2.6 and git, as well as the HDF5 development headers. For more details read the INSTALL file

Currently there is no support for RMINC on windows

Tutorials

RMINC provides learning material:

Voxel-wise Statistics (somewhat out of date): https://rawgit.com/Mouse-Imaging-Centre/RMINC/master/inst/documentation/VBMstats.pdf

How RMINC Parallel Works: https://rawgit.com/Mouse-Imaging-Centre/RMINC/master/inst/documentation/RMINC_Parallelism.html

RMINC 2D Visualization: https://rawgit.com/Mouse-Imaging-Centre/RMINC/master/inst/documentation/visualizationTutorial.html

Visualizing 3D Objects with RMINC: https://rawgit.com/Mouse-Imaging-Centre/RMINC/master/inst/documentation/RMINC_rgl.html

Analyzing Anatomy with Hierarchical Atlases: https://rawgit.com/Mouse-Imaging-Centre/RMINC/master/inst/documentation/hierarchiesTutorial.html

Development Version:

RMINC is continually evolving, you can try the newest development version with

library(devtools)
install_github("Mouse-Imaging-Centre/RMINC@develop"
  , upgrade_dependencies = FALSE)