regressionMatchImage: Image intensity normalization using linear regression.

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

Image intensity normalization using linear regression.

Description

Image intensity normalization by regressing the image intensities of the reference image with the source image.

Usage

regressionMatchImage(
  sourceImage,
  referenceImage,
  mask = NULL,
  polyOrder = 1,
  truncate = TRUE
)

Arguments

sourceImage	image whose intensities we will match to the referenceImage intensities.
referenceImage	defines the reference intensity function.
mask	Defines voxels for regression modeling.
polyOrder	of polynomial fit. Default is 1 (linear fit).
truncate	boolean which turns on/off the clipping of intensities.

Value

the sourceImage matched to the referenceImage.

Author(s)

Avants BB

Examples

library(ANTsRCore)
sourceImage <- antsImageRead( getANTsRData( "r16" ) )
referenceImage <- antsImageRead( getANTsRData( "r64" ) )
matchedImage <- regressionMatchImage( sourceImage, referenceImage )
bad_source = sourceImage[1:200, 1:200]
testthat::expect_error(regressionMatchImage( bad_source, referenceImage ))

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