Read volume file in MGH, MGZ or NIFTI format

Read multi-dimensional brain imaging data from a file.

Usage

read.fs.volume(
  filepath,
  format = "auto",
  flatten = FALSE,
  with_header = FALSE,
  drop_empty_dims = FALSE
)

Arguments

filepath

string. Full path to the input MGZ, MGH or NIFTI file.

format

character string, one one of 'auto', 'nii', 'mgh' or 'mgz'. The format to assume. If set to 'auto' (the default), the format will be derived from the file extension.

flatten

logical. Whether to flatten the return volume to a 1D vector. Useful if you know that this file contains 1D morphometry data.

with_header

logical. Whether to return the header as well. If TRUE, return an instance of class fs.volume for data with at least 3 dimensions, a named list with entries "data" and "header". The latter is another named list which contains the header data. These header entries exist: "dtype": int, one of: 0=MRI_UCHAR; 1=MRI_INT; 3=MRI_FLOAT; 4=MRI_SHORT. "voldim": integer vector. The volume (=data) dimensions. E.g., c(256, 256, 256, 1). These header entries may exist: "vox2ras_matrix" (exists if "ras_good_flag" is 1), "mr_params" (exists if "has_mr_params" is 1). See the mghheader.* functions, like mghheader.vox2ras.tkreg, to compute more information from the header fields.

drop_empty_dims

logical, whether to drop empty dimensions of the returned data

Value

data, multi-dimensional array. The brain imaging data, one value per voxel. The data type and the dimensions depend on the data in the file, they are read from the header. If the parameter flatten is TRUE, a numeric vector is returned instead. Note: The return value changes if the parameter with_header is TRUE, see parameter description.

See also

To derive more information from the header, see the mghheader.* functions, like mghheader.vox2ras.tkreg.

Other morphometry functions: fs.get.morph.file.ext.for.format(), fs.get.morph.file.format.from.filename(), read.fs.curv(), read.fs.mgh(), read.fs.morph(), read.fs.morph.gii(), read.fs.weight(), write.fs.curv(), write.fs.label.gii(), write.fs.mgh(), write.fs.morph(), write.fs.morph.asc(), write.fs.morph.gii(), write.fs.morph.ni1(), write.fs.morph.ni2(), write.fs.morph.smp(), write.fs.morph.txt(), write.fs.weight(), write.fs.weight.asc()

Examples

brain_image <- system.file("extdata", "brain.mgz",
  package = "freesurferformats",
  mustWork = TRUE
)
vd <- read.fs.volume(brain_image)
cat(sprintf(
  "Read voxel data with dimensions %s. Values: min=%d, mean=%f, max=%d.\n",
  paste(dim(vd), collapse = " "), min(vd), mean(vd), max(vd)
))
#> Read voxel data with dimensions 256 256 256 1. Values: min=0, mean=7.214277, max=156.
# Read it again with full header data:
vdh <- read.fs.volume(brain_image, with_header = TRUE)
# Use the vox2ras matrix from the header to compute RAS coordinates at CRS voxel (0, 0, 0):
vox2ras_matrix <- mghheader.vox2ras(vdh)
vox2ras_matrix %*% c(0, 0, 0, 1)
#>           [,1]
#> [1,] 127.50005
#> [2,] -98.62726
#> [3,]  79.09527
#> [4,]   1.00000