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,
  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.
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 Nov. 25, 2024, 10:27 p.m.