hyperMapp3rSegmentation: hyperMapp3rSegmentation

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

hyperMapp3rSegmentation

Description

Perform HyperMapp3r (white matter hyperintensity) segmentation described in

Usage

hyperMapp3rSegmentation(
  t1,
  flair,
  doPreprocessing = TRUE,
  numberOfMonteCarloIterations = 30,
  antsxnetCacheDirectory = NULL,
  verbose = FALSE
)

Arguments

t1	input 3-D t1-weighted MR image. Assumed to be aligned with the flair.
flair	input 3-D flair MR image. Assumed to be aligned with the t1.
doPreprocessing	perform preprocessing. See description above.
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.

Details

https://pubmed.ncbi.nlm.nih.gov/35088930/

with models and architecture ported from

https://github.com/AICONSlab/HyperMapp3r

Additional documentation and attribution resources found at

https://hypermapp3r.readthedocs.io/en/latest/

Preprocessing consists of:

• n4 bias correction and

• brain extraction. The input T1 should undergo the same steps. If the input T1 is the raw T1, these steps can be performed by the internal preprocessing, i.e. set doPreprocessing = TRUE

Value

white matter hyperintensity probability mask

Author(s)

Tustison NJ

Examples

## Not run: 
library( ANTsRNet )
library( keras )

wmh <- hyperMapp3rSegmentation( image, verbose = TRUE )

## End(Not run)

ANTsX/ANTsRNet documentation built on April 28, 2024, 12:16 p.m.