Brain extraction

Perform T1, FA, or bold brain extraction using a U-net architecture training data. "NoBrainer" is also possible where brain extraction uses U-net and FreeSurfer training data ported from the

brainExtraction(
  image,
  modality = c("t1", "t1.v0", "t1.v1", "t1nobrainer", "t1combined", "t2", "t2.v0",
    "t2star", "flair", "flair.v0", "bold", "bold.v0", "fa", "fa.v0", "t1t2infant",
    "t1infant", "t2infant"),
  antsxnetCacheDirectory = NULL,
  verbose = FALSE
)

Arguments

image	input 3-D brain image (or list of images for multi-modal scenarios).
modality	image type. Options include: "t1": T1-weighted MRI---ANTs-trained. Previous versions are specified as "t1.v0", "t1.v1". "t1nobrainer": T1-weighted MRI---FreeSurfer-trained: h/t Satra Ghosh and Jakub Kaczmarzyk. "t1combined": Brian's combination of "t1" and "t1nobrainer". One can also specify "t1combinedX" where X is the morphological radius. X = 12 by default. "flair": FLAIR MRI. "t2": T2-w MRI. "bold": 3-D mean BOLD MRI. "fa": Fractional anisotropy. "t1t2infant": Combined T1-w/T2-w infant MRI h/t Martin Styner. "t1infant": T1-w infant MRI h/t Martin Styner. "t2infant": T2-w infant MRI h/t Martin Styner.
antsxnetCacheDirectory	destination directory for storing the downloaded template and model weights. Since these can be resused, if is.null(antsxnetCacheDirectory), these data will be downloaded to the subdirectory ~/.keras/ANTsXNet/.
verbose	print progress.

Value

brain probability mask (ANTsR image)

Details

https://github.com/neuronets/nobrainer-models

Author

Tustison NJ

Examples

if (FALSE) {
library( ANTsRNet )
library( keras )

image <- antsImageRead( "t1w_image.nii.gz" )
probabilityMask <- brainExtraction( image, modality = "t1" )
}