R/reho.R

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

#' REHO
#'
#' regional homogeneity for a time series image
#'
#' @param rsfmri antsImage usually 4D
#' @param mask antsImage binary mask
#' @param shifter size of neighborhood
#' @param method one of kendall, spearman or pearson
#' @param maxDistance maximum distance from center voxel
#'
#' @return antsImage is output
#' @author Tustison, N.
#' @references Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L., 2004. Regional
#' homogeneity approach to fMRI data analysis. Neuroimage 22, 394-400.
#' @examples
#' \dontrun{
#' rehoimg <- reho(rsfmri)
#' }
#' @export reho
reho <- function(
    rsfmri, mask, shifter = 1,
    method = "kendall",
    maxDistance = 1.1) {
  if (!usePkg("magic")) stop("Need magic package")
  if (missing(mask)) {
    mask <- getMask(getAverageOfTimeSeries(rsfmri))
  }
  ndim <- length(dim(rsfmri))
  myshifts <- getNeighborhoodInMask(mask, mask, rep(shifter, ndim - 1),
    spatial.info = TRUE
  )$offsets
  mydistance <- rep(0.0, nrow(myshifts))
  for (k in 1:nrow(myshifts))
  {
    mydistance[k] <- sqrt(sum(as.numeric(myshifts[k, ])^2.0))
  }
  basemat <- timeseries2matrix(rsfmri, mask)
  corimg <- antsImageClone(mask)
  corvec <- mask[mask == 1] * 0
  ct <- 0
  for (k in 1:nrow(myshifts))
  {
    ss <- myshifts[k, ]
    if ((mydistance[k] < maxDistance) & (mydistance[k] > 1.e-9)) {
      locshiftarr <- c(ss, 0)
      rsfmris <- antsCopyImageInfo(rsfmri, as.antsImage(magic::ashift(as.array(rsfmri), locshiftarr)))
      mshift <- timeseries2matrix(rsfmris, mask)
      for (i in 1:ncol(basemat))
      {
        temp <- cor.test(basemat[, i], mshift[, i], method = method, alternative = "t")
        corvec[i] <- corvec[i] + temp$estimate
      }
      print(locshiftarr)
      ct <- ct + 1
    }
  }
  corimg[mask == 1] <- corvec / as.numeric(ct)
  return(corimg)
}