--- a
+++ b/R/deepbleed.R
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+#' DeepBleed Model
+#'
+#' @param outdir Output directory for `DeepBleed` model
+#'
+#' @note \url{https://github.com/muschellij2/deepbleed}
+#'
+#' @return A list of the output images and predictions.
+#' @export
+#' @rdname deepbleed
+#'
+#' @examples
+#' \donttest{
+#' destfile = file.path(tempdir(), "01.tar.xz")
+#' dl = download.file(
+#'   "https://archive.data.jhu.edu/api/access/datafile/1311?gbrecs=true",
+#'   destfile = destfile)
+#' res = untar(tarfile = destfile, exdir = tempdir())
+#' fname = file.path(tempdir(), "01", "BRAIN_1_Anonymized.nii.gz")
+#' mask = file.path(tempdir(), "01", "BRAIN_1_Anonymized_Mask.nii.gz")
+#' tdir = tempfile()
+#' dir.create(tdir)
+#' download_deepbleed_model(outdir = tdir)
+#' mod = load_deepbleed_model(outdir = tdir)
+#' predict_deepbleed(fname, mask = mask, outdir = tdir)
+#' }
+download_deepbleed_model = function(outdir = NULL) {
+  if (is.null(outdir)) {
+    outdir = system.file(package = "ichseg")
+  }
+  fnames = c("_index", "_data-00000-of-00002",
+             "checkpoint", "_data-00001-of-00002")
+  real_fnames = sub("_", ".", fnames)
+
+  outfiles = file.path(outdir, real_fnames)
+  if (!all(file.exists(outfiles))) {
+    url = paste0("https://www.dropbox.com/s/v2ptd9mfpo13gcb/",
+                 "mistie_2-20200122T175000Z-001.zip?dl=1")
+    tfile = tempfile(fileext = ".zip")
+    dl = utils::download.file(url, destfile = tfile)
+
+    ofiles_list = utils::unzip(
+      tfile,
+      exdir = outdir,
+      list = TRUE,
+      junkpaths = TRUE)
+    ofiles = utils::unzip(tfile, exdir = outdir, junkpaths = TRUE)
+    stopifnot(all(basename(ofiles) == fnames))
+    file.rename(ofiles, outfiles)
+  }
+  stopifnot(all(file.exists(outfiles)))
+
+  outdir = path.expand(outdir)
+  outdir = normalizePath(outdir)
+  if (!grepl("/$", outdir)) {
+    outdir = paste0(outdir, "/")
+  }
+  return(outdir)
+}
+
+#' @rdname deepbleed
+#' @export
+load_deepbleed_model = function(outdir = NULL) {
+  outdir = download_deepbleed_model(outdir)
+  path = system.file("deepbleed", package = "ichseg")
+  if (!requireNamespace("reticulate", quietly = TRUE)) {
+    stop("You need the reticulate package for deepbleed")
+  }
+  model = reticulate::import_from_path("models.vnet", path)
+  vnet = model$VNet()
+  vnet$load_weights(outdir)
+  vnet
+}
+
+#' @rdname deepbleed
+#' @param image image to segment using `DeepBleed` model
+#' @param mask brain mask image
+#' @param verbose print diagnostic messages
+#' @param ... additional arguments to send to
+#' \code{\link{CT_Skull_Stripper_mask}}
+#' @export
+predict_deepbleed = function(image,
+                             mask = NULL,
+                             verbose = TRUE,
+                             ...,
+                             outdir = NULL) {
+
+  if (verbose) {
+    message("Loading DeepBleed Model")
+  }
+  L = register_deepbleed(
+    image = image,
+    mask = mask,
+    verbose = verbose,
+    ...)
+  image = L$template_space
+  reg = L$registration
+  ss = L$skull_stripped
+  image = array(image, dim = c(1L, dim(image), 1L))
+
+
+  vnet = load_deepbleed_model(outdir = outdir)
+  if (verbose) {
+    message("Prediction")
+  }
+
+  prediction = vnet$predict(image)
+
+  arr = drop(prediction)
+  arr = neurobase::copyNIfTIHeader(arr =  arr, img = L$template_space)
+  if (verbose) {
+    message("Projecting back into Native Space")
+  }
+  native = extrantsr::ants_apply_transforms(
+    fixed = ss,
+    moving = arr,
+    interpolator = "nearestNeighbor",
+    transformlist = reg$invtransforms,
+    verbose = verbose > 1,
+    whichtoinvert = 1)
+  L$registration_matrix = reg$fwdtransforms
+  L$registration = NULL
+  L$native_prediction = native
+  L$template_prediction = arr
+  return(L)
+
+}
+
+#' @rdname deepbleed
+#' @param interpolator interpolation done for antsApplyTransforms
+#' @export
+register_deepbleed = function(
+  image,
+  mask = NULL,
+  verbose = TRUE,
+  interpolator = "Linear",
+  ...) {
+
+  image = check_nifti(image)
+  if (is.null(mask)) {
+    if (verbose) {
+      message("Skull Stripping")
+    }
+    mask = CT_Skull_Stripper_mask(image, verbose = verbose, ...)
+    mask = mask$mask
+  }
+  mask = check_nifti(mask)
+  if (verbose) {
+    message("Masking Image")
+  }
+  ss = mask_img(image, mask)
+  template.file = system.file(
+    'scct_unsmooth_SS_0.01_128x128x128.nii.gz',
+    package = 'ichseg')
+  if (verbose) {
+    message("Registration")
+  }
+  reg = extrantsr::registration(
+    ss,
+    template.file = template.file,
+    typeofTransform = "Rigid",
+    affSampling = 64,
+    interpolator = interpolator,
+    verbose = verbose > 1)
+  temp_space = reg$outfile
+
+  L = list(
+    skull_stripped = ss,
+    brain_mask = mask,
+    template_space = temp_space,
+    registration = reg
+  )
+}