R/ants_to_template.R

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

ants_to_template <- function(dim = 0, fixed_img = "", moving_img = "", timeseries_img = "", max_iterations = "30x90x20") {
  if (dim == 0) {
    print(" Problem with specified image-dimension ")
    print(" USAGE ::  ")
    print(" ants_to_template(dim=<image-dimension>,fixed_img=<fixed-image>,moving_img=<moving-image>,timeseries_img=<time-series-image>,[max_iterations=<max-iterations>")
    print(" Max-Iterations in form :    JxKxL where ")
    print(" J = max iterations at coarsest resolution (here, reduce by power of 2^2) ")
    print(" K = middle resolution iterations ( here, reduce by power of 2 ) ")
    print(" L = fine resolution iterations ( here, full resolution ) -- this level takes much more time per iteration ")
    print(" an extra  Ix before JxKxL would add another level ")
    print(" Default max-iterations is ", max_iterations, " --you can often get away with fewer for many apps ")
    print(" Other parameters are updates of the defaults used in the A. Klein evaluation paper in Neuroimage, 2009 ")
    return
  }
  
  if (nchar(fixed_img) == 0) {
    print(" Problem with specified Fixed Image ")
    print(" USAGE ::  ")
    print(" ants_to_template(dim=<image-dimension>,fixed_img=<fixed-image>,moving_img=<moving-image>,timeseries_img=<time-series-image>,[max_iterations=<max-iterations>")
    print(" Max-Iterations in form :    JxKxL where ")
    print(" J = max iterations at coarsest resolution (here, reduce by power of 2^2) ")
    print(" K = middle resolution iterations ( here, reduce by power of 2 ) ")
    print(" L = fine resolution iterations ( here, full resolution ) -- this level takes much more time per iteration ")
    print(" an extra  Ix before JxKxL would add another level ")
    print(" Default max-iterations is ", max_iterations, " --you can often get away with fewer for many apps ")
    print(" Other parameters are updates of the defaults used in the A. Klein evaluation paper in Neuroimage, 2009 ")
    return
  }
  
  if (nchar(moving_img) == 0) {
    print(" Problem with specified Moving Image ")
    print(" USAGE ::  ")
    print(" ants_to_template(dim=<image-dimension>,fixed_img=<fixed-image>,moving_img=<moving-image>,timeseries_img=<time-series-image>,[max_iterations=<max-iterations>")
    print(" Max-Iterations in form :    JxKxL where ")
    print(" J = max iterations at coarsest resolution (here, reduce by power of 2^2) ")
    print(" K = middle resolution iterations ( here, reduce by power of 2 ) ")
    print(" L = fine resolution iterations ( here, full resolution ) -- this level takes much more time per iteration ")
    print(" an extra  Ix before JxKxL would add another level ")
    print(" Default max-iterations is ", max_iterations, " --you can often get away with fewer for many apps ")
    print(" Other parameters are updates of the defaults used in the A. Klein evaluation paper in Neuroimage, 2009 ")
    return
  }
  
  if (nchar(timeseries_img) == 0) {
    print(" Problem with specified TimeSeries Image ")
    print(" USAGE ::  ")
    print(" ants_to_template(dim=<image-dimension>,fixed_img=<fixed-image>,moving_img=<moving-image>,timeseries_img=<time-series-image>,[max_iterations=<max-iterations>")
    print(" Max-Iterations in form :    JxKxL where ")
    print(" J = max iterations at coarsest resolution (here, reduce by power of 2^2) ")
    print(" K = middle resolution iterations ( here, reduce by power of 2 ) ")
    print(" L = fine resolution iterations ( here, full resolution ) -- this level takes much more time per iteration ")
    print(" an extra  Ix before JxKxL would add another level ")
    print(" Default max-iterations is ", max_iterations, " --you can often get away with fewer for many apps ")
    print(" Other parameters are updates of the defaults used in the A. Klein evaluation paper in Neuroimage, 2009 ")
    return
  }
  
  # split the string into filename and extension
  split_img <- strsplit(timeseries_img, ".", fixed = TRUE)[[1]]
  filename <- split_img[1]
  if (length(split_img) == 2) {
    extension <- paste("", split_img[2], sep = ".")
  } else if (length(split_img) == 3) {
    extension <- paste("", split_img[2], split_img[3], sep = ".")
  }
  
  ANTS(dim, "-m", paste("CC[", paste(fixed_img, moving_img, 1, 3, sep = ","), "]", sep = ""), "-t", "SyN[0.25]", 
    "-r", "Gauss[3,0]", "-o", filename, "--use-Histogram-Matching", "-i", max_iterations, "--number-of-affine-iterations", 
    "10000x10000x1000")
  
  deformed_img <- paste(filename, "deformed", extension, sep = "")
  warp_img <- paste(filename, "Warp", extension, sep = "")
  affine_txt <- paste(filename, "Affine", ".txt", sep = "")
  WarpTimeSeriesImageMultiTransform(4, moving_img, deformed_img, warp_img, affine_txt, "-R", fixed_img)
}