simple_voxel_based_analysis: Perform voxel-based population analysis between two groups.

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

Description

Student's t-test performed at each voxel within a specified mask region to determine difference between a control group and an experimental group.

Usage

simple_voxel_based_analysis <- function( dimensionality = 3, imageFileNames = c(), predictors,
  formula, testType = c( "lm", "student.t", "wilcox" ), maskFileName = "", outputPrefix = "./ANTsR" )

Arguments

To be defined in the script:

dimensionality	Dimension of images.
imageFileNames	List of image files.
testType	A value of 'lm', 'student.t', or 'wilcox'. The latter two test types are assumed to be two-sampled parametric and non-parametric, respectively.
predictors	A simple vector or single column matrix or data frame specifying sample membership for student.t or wilcox testing. For the 'lm' option, a data frame must be specified whose column names match the specified formula.
formula	Used with the 'lm' option for more sophisticated modeling.
maskFileName	File name of mask defining the region over which testing is performed (foreground voxel != 0, background voxel = 0)
outputPrefix	Output directory and prefix to prepend to the resulting image file names (t-value image, "one minus" p-value image, and "one minus" (false discovery rate) corrected p-value image.

Value

None.

Author(s)

Tustison NJ

Examples

## Not run: 
# Get the image files
controlFileNames <- list.files( path = "./example_images/", pattern =
  glob2rx( "phantomtemplate_CONTROL*" ), full.names = TRUE, recursive = FALSE )
experimentalFileNames <- list.files( path = "./example_images/", pattern =
  glob2rx( "phantomtemplate_EXP*" ), full.names = TRUE, recursive = FALSE )

images <- c( controlFileNames, experimentalFileNames )
diagnosis <- c( rep( 1, length( controlFileNames ) ), rep( 0, length( experimentalFileNames ) ) )
age <- runif( length( diagnosis ), 25, 30 )
outputPath <- "./test_output/"

prefix <- "ANTsR_t.test_"
simple_voxel_based_analysis( dimensionality = 2, imageFileNames = images,
  predictors = data.frame( diagnosis ),
  maskFileName = "./example_images/phantomtemplate_mask.nii.gz",
  outputPrefix = paste( outputPath, prefix, sep = '' ), testType = 'student.t' )

prefix <- "ANTsR_wilcox_"
simple_voxel_based_analysis( dimensionality = 2, imageFileNames = images,
  predictors = data.frame( diagnosis ),
  maskFileName = "./example_images/phantomtemplate_mask.nii.gz",
  outputPrefix = paste( outputPath, prefix, sep = '' ), testType = 'wilcox' )

prefix <- "ANTsR_lm_"
simple_voxel_based_analysis( dimensionality = 2, imageFileNames = images,
  predictors = data.frame( cbind( diagnosis, age ) ), formula = as.formula( value ~ 1 + diagnosis + age ),
  maskFileName = "./example_images/phantomtemplate_mask.nii.gz",
  outputPrefix = paste( outputPath, prefix, sep = '' ), testType = 'lm' )

## End(Not run)

stnava/itkImageR documentation built on May 30, 2019, 7:21 p.m.