R/timeseriesN3.R

In neuroconductor/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

#' Run N3 on slices of timeseries.
#'
#' Repeatedly run N3 on slices of time series and return image
#'
#'
#' @param boldimg input matrix
#' @param mask mask to use
#' @param ncorrections levels at which to apply n3
#' @return antsImage is output
#' @author Avants BB
#' @examples
#'
#'   bold<-makeImage( c(10,10,10,4), rnorm(4000) )
#'   mask<-getMask( getAverageOfTimeSeries( bold ) )
#'   boldn3<-timeseriesN3( bold, mask, c(4,2) )
#'
#' @export timeseriesN3
timeseriesN3 <- function(boldimg, mask, ncorrections = c( 2, 2 ) ) {
  dim <- 4
  ismatrix <- TRUE
  if ( "antsImage" %in% class( boldimg ) ) {
    dim <- boldimg@dimension
    if (dim != 4) {
      return(NA)
    }
    mat <- timeseries2matrix( boldimg, mask )
    ismatrix <- FALSE
  }
  if ( "matrix" %in% class(boldimg) ) {
    mat <- boldimg
  }
  for ( i in 1:nrow(mat) ) {
    perf <- makeImage( mask, mat[i, ] )
    for ( nc in ncorrections )
      {
      perf<-n3BiasFieldCorrection( perf, as.numeric( nc ) )
      }
    mat[i, ] <- perf[ mask >= 1 ]
  }
  if (ismatrix)
    return( mat )
  if (!ismatrix)
    return( matrix2timeseries( boldimg, mask, mat ) )
}