--- a
+++ b/R/ear_mask.R
@@ -0,0 +1,203 @@
+#' @rdname ear_mask
+#' @title Create Mask of the Ears
+#' @aliases ct_ear_mask,mri_ear_mask
+#' @description Creates a rough mask of the ear from a head scan
+#'
+#' @param file File for face masking - either filename or class nifti
+#' @param mask file or \code{nifti} to mask the \code{file}
+#' @param robust If \code{mask = NULL}, then \code{robust} is
+#' passed to \code{\link{CT_Skull_Stripper}}
+#' @param template.file Template to warp to original image space
+#' @param template.ear_mask Mask of template to use as rough ear mask.  If
+#' \code{template.file} is not specified, \code{template.left_ear_inds} and
+#' \code{template.right_ear_inds}
+#' must be
+#' @param template.left_ear_inds List of length 3 for indices of
+#' \code{template.file} to indicate the left-ear mask.
+#' @param template.right_ear_inds List of length 3 for indices of
+#' \code{template.file} to indicate the right-ear mask.
+#' @param extend_left after transformation, should the mask be extended to the
+#' left of the image to ensure all left ear has been removed?
+#' @param extend_right after transformation, should the mask be extended to the
+#' right of the image to ensure all right ear has been removed?
+#' @param typeofTransform Transformation for template to image, passed to
+#' \code{\link{ants_regwrite}}.
+#' @param swapdim Should the dimensions be swapped before registration,
+#' and then reset after
+#' @param skull_strip Should the data require skull stripping if
+#' no mask is provided?
+#' @param verbose Print out diagnostic messages
+#' @param ... arguments passed to \code{\link{CT_Skull_Stripper}}
+#' @export
+#' @return Object of class nifti
+#' @examples \dontrun{
+#' file = "~/Desktop/Desktop/scratch/100-318_20070723_0957_CT_3_CT_Head-.nii.gz"
+#' mask = NULL
+#' robust = FALSE
+#' ears = ct_ear_mask(
+#'    file = file,
+#'    robust = FALSE
+#'  )
+#'  img = readnii(file)
+#'  rimg = randomize_mask(img, mask = ears)
+#' }
+ct_ear_mask = function(
+  file,
+  skull_strip = TRUE,
+  mask = NULL,
+  robust = TRUE,
+  template.file =
+    system.file(
+      "scct_unsmooth_SS_0.01.nii.gz",
+      package = "ichseg"),
+  template.ear_mask = NULL,
+  template.left_ear_inds = list(170:180, 60:110, 1:60),
+  template.right_ear_inds = list(1:10, 60:110, 1:60),
+  extend_left = TRUE,
+  extend_right = TRUE,
+  typeofTransform = "Affine",
+  swapdim = TRUE,
+  verbose = TRUE,
+  ...){
+
+  if (skull_strip) {
+    mask = .make_ss_mask(file = file,
+                         mask = mask,
+                         verbose = verbose,
+                         robust = robust,
+                         template.file = template.file, ...)
+  }
+
+  template.left_ear_mask = .make_template_mask(
+    template.file = template.file,
+    template.mask = template.ear_mask,
+    template.inds = template.left_ear_inds)
+  template.right_ear_mask = .make_template_mask(
+    template.file = template.file,
+    template.mask = template.ear_mask,
+    template.inds = template.right_ear_inds)
+
+  template.ear_mask = template.left_ear_mask | template.right_ear_mask
+
+  L = .mask_reg(file = file,
+                mask = mask,
+                verbose = verbose,
+                swapdim = swapdim,
+                template.file = template.file,
+                typeofTransform = typeofTransform,
+                template.mask = template.ear_mask)
+
+  mask_trans = L$mask_trans
+  img = L$img
+
+
+  ######################################
+  # Applying the mask to the image
+  ######################################
+  mask_trans = mask_trans > 0.5
+  any_in_mask = any(mask_trans)
+  ind = which(mask_trans, arr.ind = TRUE)
+  dimg = dim(img)
+  xdim = dimg[1]
+  midx = xdim/2
+  if (extend_left || extend_right) {
+    if (any_in_mask) {
+      df = data.frame(ind)
+      df$left = c("left", "right")[ (df$dim1 > midx) + 1]
+      ss = split(df, df$left)
+      ss = lapply(ss, function(x) {
+        x$left = NULL
+        x
+      })
+      inds = NULL
+      ind = ss$left
+      if (!is.null(ind) && nrow(ind) > 0) {
+        xs = seq(1, max(ind$dim1)) # for left
+        ys = unique(ind$dim2)
+        zs = unique(ind$dim3)
+        run_inds = expand.grid(xs, ys, zs)
+        run_inds = as.matrix(run_inds)
+      }
+      inds = rbind(inds, run_inds)
+
+      ind = ss$right
+      if (!is.null(ind) && nrow(ind) > 0) {
+        xs = seq(min(ind$dim1), xdim) # for right
+        ys = unique(ind$dim2)
+        zs = unique(ind$dim3)
+        run_inds = expand.grid(xs, ys, zs)
+        run_inds = as.matrix(run_inds)
+      }
+      inds = rbind(inds, run_inds)
+
+      newimg = niftiarr(img, 0)
+      newimg[inds] = 1
+      newimg = cal_img(newimg)
+    } else {
+      warning("No registered object in mask found - cannot extend!")
+      newimg = mask_trans
+    }
+  } else {
+    newimg = mask_trans
+  }
+
+
+  if (swapdim) {
+    if (verbose) {
+      message(paste0("# Swapping Dimensions Back\n"))
+    }
+    sorient = L$sorient
+    ori = L$ori
+    newimg = reverse_rpi_orient(
+      file = newimg,
+      convention = ori,
+      orientation = sorient,
+      verbose = verbose)
+  }
+  return(newimg)
+}
+
+
+
+#' @rdname ear_mask
+#' @export
+mri_ear_mask = function(
+  ...,
+  skull_strip = TRUE,
+  mask = NULL,
+  robust = FALSE,
+  template.file = mni_fname(brain = skull_strip)
+){
+
+  L = list(...)
+  L$robust = robust
+  L$skull_strip = skull_strip
+  L$mask = mask
+  L$template.file = template.file
+
+  if (is.null(mask) & skull_strip) {
+    func = function(L, arg, opt) {
+      nL = names(L)
+      if (!arg %in% nL) {
+        L[arg] = opt
+      }
+      return(L)
+    }
+    uthresh = L$uthresh
+    if (is.null(uthresh)) {
+      file = L$file
+      if (is.null(file)) {
+        file = L[[1]]
+      }
+      uthresh = fslr::fslmax(file)
+      L$uthresh = uthresh
+    }
+
+    L = func(L, "presmooth", FALSE)
+    L = func(L, "remask", FALSE)
+    L = func(L, "inskull_mesh", FALSE)
+    L = func(L, "opts", "-v")
+  }
+  res = do.call("ct_ear_mask", args = L)
+  return(res)
+}