wmhSegmentation: White matter hyperintensity probabilistic segmentation

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

White matter hyperintensity probabilistic segmentation

Description

Perform white matter hyperintensity probabilistic segmentation using deep learning

Usage

wmhSegmentation(
  flair,
  t1,
  whiteMatterMask = NULL,
  useCombinedModel = TRUE,
  predictionBatchSize = 16,
  patchStrideLength = 32,
  doPreprocessing = TRUE,
  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).
whiteMatterMask	input white matter mask for patch extraction. If None, calculated using deepAtropos (labels 3 and 4).
useCombinedModel	Original or combined.
predictionBatchSize	Control memory usage for prediction. More consequential for GPU-usage.
patchStrideLength	3-D vector or int. Dictates the stride length for accumulating predicting patches.
doPreprocessing	perform n4 bias correction, intensity truncation, brain extraction.
verbose	print progress.

Value

probabilistic image.

Author(s)

Tustison NJ

Examples

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

t1 <- antsImageRead( "t1.nii.gz" )
flair <- antsImageRead( "flair.nii.gz" )
results <- wmhSegmentation( t1, flair )

## End(Not run)

ANTsX/ANTsRNet documentation built on Nov. 21, 2024, 4:07 a.m.