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RNiftyReg (version 2.8.4)

niftyreg: Two and three dimensional image registration

Description

The niftyreg function performs linear or nonlinear registration for two and three dimensional images. 4D images may also be registered volumewise to a 3D image, or 3D images slicewise to a 2D image. This function is a common wrapper for niftyreg.linear and niftyreg.nonlinear.

Usage

niftyreg(source, target, scope = c("affine", "rigid", "nonlinear"),
  init = NULL, sourceMask = NULL, targetMask = NULL, symmetric = TRUE,
  interpolation = 3L, estimateOnly = FALSE, sequentialInit = FALSE,
  internal = NA, precision = c("double", "single"),
  threads = getOption("RNiftyReg.threads"), ...)

# S3 method for niftyreg asNifti(x, ...)

# S3 method for niftyreg as.array(x, ...)

Value

A list of class "niftyreg" with components:

image

An array or internal image representing the registered and resampled source image in the space of the target image. This element is NULL if the estimateOnly parameter is TRUE.

forwardTransforms

A list of (linear or nonlinear) transformations from source to target space.

reverseTransforms

A list of (linear or nonlinear) transformations from target to source space.

iterations

A list of integer vectors, giving the number of iterations completed at each ``level'' of the algorithm. Note that for the first level of the linear algorithm specifically, twice the specified number of iterations is allowed.

source

An internal representation of the source image for each registration.

target

An internal representation of the target image.

The as.array method for this class returns the image

element.

Arguments

source

The source image, an object of class "nifti" or "internalImage", or a plain array, or a NIfTI-1 filename. Must have 2, 3 or 4 dimensions.

target

The target image, an object of class "nifti" or "internalImage", or a plain array, or a NIfTI-1 filename. Must have 2 or 3 dimensions.

scope

A string describing the scope, or number of degrees of freedom (DOF), of the registration. The currently supported values are "affine" (12 DOF), "rigid" (6 DOF) or "nonlinear" (high DOF, with the exact number depending on the image sizes).

init

Transformation(s) to be used for initialisation, which may be NULL, for no initialisation, or an affine matrix or control point image (nonlinear only). For multiple registration, where the source image has one more dimension than the target, this may also be a list whose components are likewise NULL or a suitable initial transform.

sourceMask

An optional mask image in source space, whose nonzero region will be taken as the region of interest for the registration. Ignored when symmetric is FALSE.

targetMask

An optional mask image in target space, whose nonzero region will be taken as the region of interest for the registration.

symmetric

Logical value. Should forward and reverse transformations be estimated simultaneously?

interpolation

A single integer specifying the type of interpolation to be applied to the final resampled image. May be 0 (nearest neighbour), 1 (trilinear) or 3 (cubic spline). No other values are valid.

estimateOnly

Logical value: if TRUE, transformations will be estimated, but images will not be resampled.

sequentialInit

If TRUE and source has higher dimensionality than target, transformations which are not explicitly initialised will begin from the result of the previous registration.

internal

If NA, the default, the final resampled image will be returned as a standard R array, but control point maps will be objects of class "internalImage", containing only basic metadata and a C-level pointer to the full image. (See also readNifti.) If TRUE, all image-type objects in the result will be internal images; if FALSE, they will all be R arrays. The default is fine for most purposes, but using TRUE may save memory, while using FALSE can be necessary if there is a chance that external pointers will be invalidated, for example when returning from worker threads.

precision

Working precision for the registration. Using single- precision may be desirable to save memory when coregistering large images.

threads

For OpenMP-capable builds of the package, the maximum number of threads to use.

...

Further arguments to niftyreg.linear or niftyreg.nonlinear.

x

A "niftyreg" object.

Author

Jon Clayden <code@clayden.org>

References

Please see niftyreg.linear or niftyreg.nonlinear for references relating to each type of registration.

See Also

niftyreg.linear and niftyreg.nonlinear, which do most of the work. Also, forward and reverse to extract transformations, and applyTransform to apply them to new images or points.

Examples

Run this code
if (FALSE) {
source <- readNifti(system.file("extdata", "epi_t2.nii.gz",
  package="RNiftyReg"))
target <- readNifti(system.file("extdata", "flash_t1.nii.gz",
  package="RNiftyReg"))

result <- niftyreg(source, target, scope="affine")
}

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