perfusionregression: Perfusion Regression
In stnava/itkImageR: Examples using Rcpp to interface R and ITK

Description Usage Arguments Value Author(s) Examples

Estimate CBF using standard regression and optionally robust regression.

1	perfusionregression( mask_img , mat , xideal , nuis , m0, dorobust = 0 )

`mask_img`	Mask image selects the voxels where CBF will be estimated. Voxels corresponding to logical FALSE are not computed.
`mat`	Matrix with a column for every time-series voxel. Number of rows equals the number of time units in the series.
`xideal`	1D time-series signal to be used a ideal or model for regression.
`nuis`	Nuisance parameters obtained from 'get_perfusion_predictors'.
`m0`	m0 antsImage passed in according to needs of specific ASL sequence.
`dorobust`	Real value in interval from 0 to 1. If greater than 0, then robust regression will be performed. A typical value would be 0.95 i.e. use voxels with 95 percent confidence.

Success – An object of type 'antsImage' containing the CBF estimate for voxels corresponding to the mask input

Shrinidhi KL Avants BB

## Not run: 
# predictors -- result of calling 'get_perfusion_predictors'
cbf <- perfusionregression( mask_img, mat , predictors$xideal , predictors$nuis )

## End(Not run)