volumes_lm

Compute per-voxel linear models from a training list of volumes.

volumes_lm [options] <training_list> <output_prefix>

DESCRIPTION

volumes_lm builds per-voxel linear models from a set of MINC volumes specified in a training list file. Each line of the training list contains the path to a volume and associated covariates. The tool estimates linear model coefficients at each voxel and writes the resulting coefficient volumes using the specified output prefix.

This tool is useful for building statistical models of anatomical variation across a population, where each voxel’s intensity is modeled as a linear function of the provided covariates.

OPTIONS

--verbose

Print progress information during processing.

--clobber

Overwrite existing output files.

--mask mask.mnc

Restrict the linear model computation to voxels within the specified binary mask.

--buffers n

Set the number of I/O buffers for reading input volumes. Default: 1000.

EXAMPLES

Build a linear model from a training list:

volumes_lm training_list.txt model_

Build a linear model with a mask:

volumes_lm --mask brainmask.mnc training_list.txt model_

AUTHOR

Vladimir S. Fonov - McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University.

COPYRIGHTS

Copyright © 2011 by Vladimir S. Fonov

SEE ALSO

volumes_lsq, volumes_pca