GNU R package to read and write structural neuroimaging file formats. Comes with support for file formats used by FreeSurfer, CAT12/SPM, FSL, BrainVoyager, MRtrix3, Diffusion Toolkit/TrackVis and other neuroimaging software packages.
Supported formats | Installation | Documentation | License | Citation | Development
This low-level package provides well-tested file format readers and writers for FreeSurfer neuroimaging data. Typically, you want to access not only individual files, but datasets of subjects stored in the standardized output structure of recon-all (your $SUBJECTS_DIR) when doing neuroimaging research. In that case, I recommend to use the high-level functions from the fsbrain package instead of re-inventing the wheel. The fsbrain package is built on top of freesurferformats and provides functions for working with the data of your study, including visualization of results on brain meshes.
You do not need to have FreeSurfer installed to use this package. It implements its own readers and writers for the following file formats:
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MGH/MGZ: FreeSurfer 4-dimensional brain images or arbitrary other data. Typically a single 3D brain MRI scan or a time series of scans, or morphometry data for brain surfaces. The format is named after the Massachusetts General Hospital, and the specs are given (rather implicitely) here in the FreeSurfer wiki. MGZ is just a gzipped version of MGH. An example file from the recon-all output for a subject would be
mri/T1.mgz(containing a 3D brain volume), but alsosurf/lh.area.fwhm15.fsaverage.mgh(containing surface data mapped to standard space). This format can be read and written. Reading and writing header data is also supported, and transforms like the ras2vox matrix can be computed from the header, allowing for the proper orientation of the voxel data in different spaces. -
FreeSurfer curv format: Morphometry data for a brain surface, one scalar per vertex. Could be the thickness or area of the cerebral cortex at each mesh vertex. Two versions of this format exist, an ASCII version and a binary version (the only one that is used in current FreeSurfer versions). An example file would be
surf/lh.area. Both versions of this format can be read and written. -
FreeSurfer annotation file format: Contains a cortical parcellation. A cortical parcellation originates from a brain atlas and contains a label for each vertex of a surface that assigns this vertex to one of a set of atlas regions. (Put another way, a parcellation splits the brain surface into disjunct atlas regions). The file format also contains a colortable, which assigns a color code to each atlas region. An example file would be
labels/lh.aparc.annot. This format can be read and written. The standard atlases that come with FreeSurfer are Desikan-Killiany (aparc), DKT (aparc.DKTatlas40), and Destrieux (aparc.a2009s). -
FreeSurfer surface file format: Contains a brain surface mesh in a binary format. Such a mesh is defined by a list of vertices (each vertex is given by its x,y,z coords) and a list of faces (each face is given by three vertex indices). An example file would be
surf/lh.white. This format can be read and written. Reading and writing the ASCII version of the FreeSurfer surface format (.ascfiles) is also supported. -
Other mesh file formats: Read and write support is available for meshes in VTK ASCII format (
.vtkfiles), Surf-Ice format (.mz3), Wavefront object format (.obj), Object File Format (.off), Brainvoyager SRF format (.srf), and Stanford triangle format (.ply). Additionally, meshes can be exported in PLY2 format (.ply2). Meshes can be imported from files in BYU format (.byu), GEO format (.geo) and TRI format (also known as ICO mesh format,.tri). -
FreeSurfer label file format: Contains a list of vertices included in a label. A label is like a mask, and is typically used to describe the vertices which are part of a certain brain region. An example file would be
label/lh.cortex.label. Volume labels are also supported. This format can be read and written. -
FreeSurfer color lookup table (LUT) file format: Contains a color lookup table in ASCII format. This LUT assigns names and RGBA color values to a set of structures (typically brain regions). LUT data can also be extracted from an annotation, and a set of labels and a LUT can be merged into an annotation. An example file would be
FREESURFER_HOME/FreeSurferColorLUT.txt. This format can be read and written. -
FreeSurfer weight file format: Contains one value per listed vertex. In contrast to curv files, weight files contain values not for all vertices of a surface, but only for a subset of vertices defined by their indices. The format is known as weight format, paint format, or simply w format. This format can be read and written.
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FreeSurfer patch file format: Contains a subset of a surface (a surface patch), given by the vertex indices (and the faces in the ASCII version). For each patch vertex, it also stores whether the vertex is part of the patch border. This format can be read and written.
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FreeSurfer spatial transformation matrices can be read from LTA, register.dat, and xfm files.
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FreeSurfer Group Descriptor (FSGD) files: please see the fsbrain package for FSGD read and write file support. This is very handy if you conducted GLM-based statistical analyses in FreeSurfer and want to visualize the results in R.
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NIFTI v1: FreeSurfer morphometry data in NIFTI v1 format (including
.niiand.nii.gz) files can be read and written with our own NIFTI v1 support. FreeSurfer NIFTI v1 files that use the (non-standard) FreeSurfer NIFTI hack are also supported. These files are created by FreeSurfer tools if NIFTI output is requested and one dimension of the data is larger than the 32k entries allowed by the NIFTI v1 standard. This affects virtually all surface-based data files because the brain surface meshes in FreeSurfer typically have more than 100k vertices. -
NIFTI v2: This package comes with its own NIFTI v2 reader and writer. The 2nd format version supports larger data dimensions and drops backwards compatibility with older NIFTI-style file formats like ANALYZE.
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Fiber track formats (DTI, diffusion tensor imaging): there is read support for the '.trk' format used by the Diffusion Toolkit / TrackVis and the '.tck' and '.tsf' formats used by MRtrix3.
We also provide wrappers and adapter functions for existing neuroimaging file format packages, which load the data into freesurferformats data structures:
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NIFTI volumes (v1, single file): Reading is supported based on the oro.nifti package. The result is transformed into an
fs.volumeinstance, including computation of transformation matrices like vox2ras from the NIFTI header q-form/s-form, so NIFTI volumes can be used just like MGH/MGZ volumes. (Note: If you do not need the FreeSurfer-style transforms and all you want is to read NIFTI files, you should useoro.niftidirectly.) Alternatively, our internal NIFTI1 reader can be used, which also supports non-standard FreeSurfer NIFTI1 files (see above). -
GIFTI: General reading is supported based on the gifti and xml2 packages. GIFTI is a very versatile format that can hold different kinds of data, and freesurferformats provides custom readers for morphometry data, surface meshes, labels and annotations. The freesurferformats also comes with GIFTI write support, including a general data array writer as well as custom writers for the previously listed kinds of neuroimaging data.
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CIFTI: Reading of morphometry data from CIFTI v2 files (
.dscalar.nii) is supported based on the cifti package by John Muschelli. The wrapper functions in freesurferformats support extraction of the data for a specific brain model (surface mesh), and map the data to the appropriate vertex indices of the surface based on the CIFTI metadata.
The package is on CRAN, so you can simply:
install.packages("freesurferformats")If you want support for as many neuroimaging file formats as possible, do this instead to install with all optional dependencies:
install.packages("freesurferformats", dependencies=TRUE);The package is also available from neuroconductor.
In case something goes wrong, don't worry. Just install the missing system dependencies and retry.
Note: You can ignore this section unless you want to build the freesurferformats package from the source code.
A system dependency is a non-R software that is needed for the installation of a package. System dependencies cannot be installed automatically using the R package system, so you need to install them manually or using the package manager of your operating system.
If you install R packages from source (the default under Linux) and want support for the GIFTI XML file format, you will need libxml2-dev. If you do not have it installed already, before installing freesurferformats, run the following command in your system shell (not in R):
- for deb-based Linux distributions (Debian, Ubuntu, ...):
sudo apt-get install libxml2-dev- for rpm-based Linux distributions (Fedora, CentOS, RHEL, ...):
sudo yum install libxml2-develBefore using any functions, of course load the package itself:
library("freesurferformats")Now you can call the following functions:
read.fs.mgh() # read volume or morphometry data from files in MGH or MGZ format, e.g., `mri/brain.mgz` or `surf/lh.area.fwhm10.fsaverage.mgh`.
read.fs.curv() # read morphometry data from 'curv' format files like `surf/lh.area`
read.fs.morph() # read any morphometry file (mgh/mgz/curv). The format is derived from the file extension.
read.fs.annot() # read annotation data or brain atlas labels from files like `label/lh.aparc.annot`
read.fs.surface() # read a surface mesh, like `surf/lh.white`, supports many standard mesh formats
read.fs.label() # read a label file, like `label/lh.cortex.label`
read.fs.colortable() # read a color lookup table (LUT), like `$FREESURFER_HOME/FreeSurferColorLUT.txt`
read.fs.weight() # read scalar data for a subset of vertices, defined by index. Known as `weight`, `paint` or simply `w` format.
read.fs.patch() # read a surface patch, which is a part of a surface.
read.fs.transform() # read spatial transformation matrix
read.dti.tck() # read DTI tracks from MRtrix3 'TCK' format
read.dti.trk() # read DTI tracks from Diffusion Toolkit/TrakVis 'TRK' format
write.fs.mgh() # write data with 1 to 4 dimensions to an MGH format file
write.fs.curv() # write a data vector to a 'curv' format file
write.fs.morph() # write any morphometry file (mgh/mgz/curv). The format is derived from the file extension.
write.fs.surface() # write a surface mesh
write.fs.label() # write a label file
write.fs.annot() # write an annotation file
write.fs.colortable() # write a color lookup table (LUT)
write.fs.weight() # write scalar vertex data in weight or w format
write.fs.patch() # write a surface patch, which is a part of a surface.The documentation is included in the package and not repeated on this website.
The documentation can be accessed from within an R session after you have loaded the freesurferformats package:
- Detailed vignettes with explanations and examples for the usage of all functions of the package are included, run
browseVignettes("freesurferformats")to see them. You can also open the vignettes directly:- learn how to read neuroimaging data:
vignette("freesurferformats")read online at CRAN - learn how to write neuroimaging data:
vignette("freesurferformats_write")read online at CRAN - learn advanced header-based operations:
vignette("freesurferformats_header")read online at CRAN
- learn how to read neuroimaging data:
- Help for a specific function can be accessed in the usual R manner:
?<function>, where you replace<function>with a function name. Like this:?read.fs.mgh. - Run
example(<function>)to see a live demo that uses the function<function>. Like this:example(read.fs.mgh). - The unit tests that come with this package are essentially a list of examples that illustrate how to use the functions.
One of the example subjects that comes with FreeSurfer is bert. The following example shows how to load Bert's brain. If you have FreeSurfer installed, you can start GNU R by typing R in your favourite terminal application and run the following commands:
install.packages("freesurferformats")
# Load volume from file
library("freesurferformats")
berts_brain = paste(Sys.getenv("FREESURFER_HOME"), "/subjects/bert/mri/brain.mgz", sep="")
mgh = read.fs.mgh(berts_brain, with_header=TRUE);
# Compute the vox2ras matrix from the header:
mghheader.vox2ras(mgh)
# [,1] [,2] [,3] [,4]
#[1,] -1 0 0 133.3997
#[2,] 0 0 1 -110.0000
#[3,] 0 -1 0 128.0000
#[4,] 0 0 0 1.0000
# ...and the data:
mean(mgh$data)
#[1] 8.214322
dim(drop(mgh$data))
# [1] 256 256 256If you do not have FreeSurfer installed and thus don't have Bert, replace berts_brain with the example brain that comes with freesurferformats:
fsf_brain = system.file("extdata", "brain.mgz", package = "freesurferformats", mustWork = TRUE);The freesurferformats package is free software, published under the MIT license.
Note: The file LICENSE in this repository is a CRAN license template only (as required by CRAN) and does not contain the full MIT license text. See the file LICENSE_FULL for the full license text.
A paper is in the making. For now, please cite the R package. You can generate the citation for the version you use by typing the following command in R:
citation("freesurferformats")
This will ouput something like this (but for the version you actually used, which is important for reproducibility):
To cite package ‘freesurferformats’ in publications use:
Tim Schäfer (2020). freesurferformats: Read and Write 'FreeSurfer'
Neuroimaging File Formats. R package version 0.1.9.
https://CRAN.R-project.org/package=freesurferformats
A BibTeX entry for LaTeX users is
@Manual{,
title = {freesurferformats: Read and Write 'FreeSurfer' Neuroimaging File Formats},
author = {Tim Schäfer},
year = {2020},
note = {R package version 0.1.9,
url = {https://CRAN.R-project.org/package=freesurferformats},
doi = {10.5281/zenodo.3540434},
url = {https://dx.doi.org/10.5281/zenodo.3540434},
}
The Digital Object Identifier (DOI) for freesurferformats is: 10.5281/zenodo.3540434. Note that this DOI always points to the latest version, so be sure to still include the package version in the citation.
A poster of freesurferformats has been presented at INSAR 2020 Annual Meeting: Abstract, ePoster
You can install the latest development version directly from Github if you need features which have not been released yet. Please run the tests before using the dev version (see the Unit tests / CI section below).
If you do not have devtools and related tools installed yet:
install.packages(c("devtools", "knitr", "rmarkdown", "testthat", "covr"));Then:
devtools::install_github("dfsp-spirit/freesurferformats", build_vignettes=TRUE)While the development versions may have new features, you should not consider their API stable. Wait for the next release if you are not fine with adapting your code to API changes later. If in doubt, do not use the dev version.
This package comes with lots of unit tests. To run them, in a clean R session:
library(devtools)
library(freesurferformats)
devtools::check()Continuous integration results:
AppVeyor CI under Windows
The displayed status represents the development version. Don't worry if you are using the stable version from CRAN and CI is currently failing.
If you found a bug, have any question, suggestion or comment on freesurferformats, please open an issue. I will definitely answer and try to help.
Please see CONTRIBUTING.md for instructions on how to contribute code.
The freesurferformats package was written by Tim Schäfer. To contact me in person, please use the maintainer email address listed on the CRAN webpage for freesurferformats.