SPM12 Realign (Estimate and Reslice)

Performs SPM12 realignment estimation and reslicing on an Image

build_spm12_realign(
  filename,
  time_points = NULL,
  fwhm = 5,
  quality = 0.9,
  separation = 4,
  register_to = c("first", "mean"),
  est_interp = c("bspline2", "trilinear", paste0("bspline", 3:7)),
  wrap_x = FALSE,
  wrap_y = FALSE,
  wrap_z = FALSE,
  weight_image = NULL,
  reslice = c("all+mean", "all", "2:n", "mean"),
  reslice_interp = c("bspline4", "nearestneighbor", "trilinear", paste0("bspline",
    2:3), paste0("bspline", 5:7), "fourier"),
  mask = FALSE,
  prefix = "r",
  verbose = TRUE,
  ...
)

spm12_realign(
  ...,
  add_spm_dir = TRUE,
  spmdir = spm_dir(verbose = verbose, install_dir = install_dir),
  clean = TRUE,
  retimg = FALSE,
  reorient = FALSE,
  verbose = TRUE,
  outdir = NULL,
  install_dir = NULL
)

Arguments

filename	Files to be realigned and resliced
time_points	A vector of time points to run realignment, If filename is a 4D file, then will do all the time points. Otherwise, filename must be a character vector of 3D files or a list of 3D nifti objects.
fwhm	Full-Width Half Max to smooth. Gaussian smoothing to apply to the 256x256 joint histogram.
quality	Quality versus speed trade-off. Highest quality (1) gives most precise results, whereas lower qualities gives faster realignment.
separation	The average distance between sampled points (in mm). Can be a vector to allow a coarse registration followed by increasingly fine
register_to	Should the files be registered to the first or the mean
est_interp	Interpolator for estimation
wrap_x	wrap in x-direction
wrap_y	wrap in y-direction
wrap_z	wrap in z-direction
weight_image	weighting image to weight each voxel of the reference image during estimation. The weights are proportional to the inverses of the standard deviations. May be used when there is a lot of motion.
reslice	Options for reslicing all - all images in filename, 2:n - all images in filename 2:length(filename), all+mean - all images and the mean, mean - mean only
reslice_interp	Interpolator for reslicing
mask	Mask the data. With masking enabled, the program searches through the whole time series looking for voxels which need to be sampled from outside the original images. Where this occurs, that voxel is set to zero for the whole set of images
prefix	Prefix to append to front of image filename
verbose	Print diagnostic messages
...	Arguments passed to run_spm12_script
add_spm_dir	Add SPM12 directory from this package
spmdir	SPM dir to add, will use package default directory
clean	Remove scripts from temporary directory after running
retimg	(logical) return image of class nifti
reorient	(logical) If retimg, should file be reoriented when read in?
outdir	Directory to copy results. If full filename given, then results will be in dirname(filename)
install_dir	directory to download SPM12

Value

List of output files, the matlabbatch object, and the script

Examples

dims = rep(10, 4)
temp_nii = array(rnorm(prod(dims)), dim = dims)
temp_nii = oro.nifti::nifti(temp_nii)
res = build_spm12_realign(temp_nii)
#> # Getting Number of Time Points
#> # Reslice is all+mean