White matter hyperintensity segmentation

Perform WMH segmentation using the winning submission in the MICCAI 2017 challenge by the sysu_media team using FLAIR or T1/FLAIR. The MICCAI challenge is discussed in

sysuMediaWmhSegmentation(
  flair,
  t1 = NULL,
  useEnsemble = TRUE,
  antsxnetCacheDirectory = NULL,
  verbose = FALSE
)

Arguments

flair	input 3-D FLAIR brain image.
t1	input 3-D T1-weighted brain image (assumed to be aligned to the flair, if specified).
useEnsemble	boolean to check whether to use all 3 sets of weights.
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 inst/extdata/ subfolder of the ANTsRNet package.
verbose	print progress.

Value

WMH segmentation probability image

Details

https://pubmed.ncbi.nlm.nih.gov/30908194/

with the sysu_media's team entry is discussed in

https://pubmed.ncbi.nlm.nih.gov/30125711/

with the original implementation available here:

\url{https://github.com/hongweilibran/wmh_ibbmTum}

The original implementation used global thresholding as a quick brain extraction approach. Due to possible generalization difficulties, we leave such post-processing steps to the user. For brain or white matter masking see functions brainExtraction or deepAtropos, respectively.

Author

Tustison NJ

Examples

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

image <- antsImageRead( "flair.nii.gz" )
probabilityMask <-sysuMediaWmhSegmentation( image )
}