simple_roi_analysis¶

purpose:

Perform ROI population analysis between two groups.

description:

Student’s t-test performed for each labeled region within a specified mask to determine difference between a control group and an experimental group.

usage:

roiResults <- simple_roi_analysis( dimensionality = 3, controlFileNames = c(),

experimentalFileNames = c(), roiLabelsFileName = “” )

examples:

# 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/"

roiResults.ttest <- simple_roi_analysis( dimensionality = 2, imageFileNames = images,

  predictors = data.frame( diagnosis ),

  roiLabelsFileName = "./example_images/phantomtemplate_roi_labels.nii.gz", testType = 'student.t' )

roiResults.wilcox <- simple_roi_analysis( dimensionality = 2, imageFileNames = images,

  predictors = data.frame( diagnosis ),

  roiLabelsFileName = "./example_images/phantomtemplate_roi_labels.nii.gz", testType = 'wilcox' )

roiResults.lm <- simple_roi_analysis( dimensionality = 2, imageFileNames = images,

  predictors = data.frame( cbind( diagnosis, age ) ), formula = as.formula( value ~ 1 + diagnosis + age ),

  roiLabelsFileName = "./example_images/phantomtemplate_roi_labels.nii.gz", testType = 'lm' )

ANTsR 0.0.0 documentation

simple_roi_analysis

simple_roi_analysis¶