affineInitializer: a multi-start optimizer for affine registration

In neuroconductor-devel/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

Description

Searches over the sphere to find a good initialization for further registration refinement, if needed. This is a wrapper for the ANTs function antsAffineInitializer.

Usage

affineInitializer(
  fixedImage,
  movingImage,
  searchFactor = 20,
  radianFraction = 0.1,
  usePrincipalAxis = FALSE,
  localSearchIterations = 10,
  mask,
  txfn,
  num_threads = 1
)

Arguments

fixedImage	the fixed reference image
movingImage	the moving image to be mapped to the fixed space
searchFactor	degree of increments on the sphere to search
radianFraction	between zero and one, defines the arc to search over
usePrincipalAxis	boolean to initialize by principal axis
localSearchIterations	gradient descent iterations
mask	optional mask to restrict registration
txfn	filename for the transformation
num_threads	will execute Sys.setenv(ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS = num_threads) before running to attempt a more reproducible result. See https://github.com/ANTsX/ANTs/wiki/antsRegistration-reproducibility-issues for discussion. If NULL, will not set anything.

Value

transformationMatrix

Note

See https://github.com/ANTsX/ANTs/issues/444 for reproducibility discussion

Author(s)

Avants BB

Examples

fi <- antsImageRead(getANTsRData("r16"))
mi <- antsImageRead(getANTsRData("r27"))
tx <- affineInitializer( fi, mi )

mi2 = resampleImage(mi, c(1.25, 1.25))
tx <- affineInitializer( fi, mi2 )
tx2 <- affineInitializer( fi, mi2 )
if ('R.matlab' %in% installed.packages()) {
tx_hdr = R.matlab::readMat(tx)
trans = tx_hdr$AffineTransform.double.2.2
fixed = tx_hdr$fixed

tx2_hdr = R.matlab::readMat(tx2)
trans2 = tx2_hdr$AffineTransform.double.2.2
fixed2 = tx2_hdr$fixed

testthat::expect_equal(tx_hdr, tx2_hdr)
}

neuroconductor-devel/ANTsR documentation built on April 1, 2021, 1:02 p.m.