A package to compute BrainPrint (shape descriptors) from FastSurfer/FreeSurfer MRI segmentations
Project description
BrainPrint
This is the brainprint
python package, a derivative of the original
BrainPrint-legacy scripts,
with the primary goal to provide a Python-only version, to integrate the
LaPy package, and to remove dependencies
on third-party software (shapeDNA-* binaries, gmsh, meshfix). As a result,
some functionality of the original BrainPrint-legacy scripts is no longer
maintained (currently no support of tetrahedral meshes and no support of
cortical parcellations or label files).
Installation
Use the following code to install the latest release of LaPy into your local Python package directory:
python3 -m pip install brainprint
This will also install the necessary dependencies, e.g. the LaPy package. You may need to add your local Python package directory to your $PATH in order to run the scripts.
Usage
Command Line Interface (CLI)
Once installed, the package provides a brainprint
executable which can be run from the command line.
The brainprint
CLI enables per-subject computation of the individual brainprint descriptors. Its usage and options are summarized below;
detailed info is available by calling the script without any arguments from the command line.
brainprint --sdir <directory> --sid <SubjectID> [--num <num>] [--evec] [--skipcortex] [--norm <surface|volume|geometry|none> ] [--reweight] [--asymmetry] [--outdir <directory>] [--help] [--more-help]
Options:
--help Show this help message and exit
--more-help Show extensive help message and exit
Required options:
--sid <SubjectID>
Subject ID (FreeSurfer-processed directory inside the
subjects directory)
--sdir <directory>
FreeSurfer subjects directory
Processing directives:
--num <num> Number of eigenvalues/vectors to compute (default: 50)
--evec Switch on eigenvector computation (default: off)
--skipcortex Skip cortical surfaces (default: off)
--norm <surface|volume|geometry|none>
Switch on eigenvalue normalization; will be either surface,
volume, or determined by the geometry of the object. Use
"none" or leave out entirely to skip normalization.
--reweight Switch on eigenvalue reweighting (default: off)
--asymmetry Perform left-right asymmetry calculation (default: off)
--cholmod Switch on use of (faster) Cholesky decomposition instead
of (slower) LU decomposition (default: off). May require
manual install of scikit-sparse package.
Output parameters:
--outdir=OUTDIR Output directory (default: <sdir>/<sid>/brainprint)
--keep-temp Whether to keep the temporary files directory or not
by default False
Python Package
brainprint
can also be run within a pure Python environment, i.e. installed and imported as a Python package. E.g.:
>>> from brainprint import Brainprint
>>> subjects_dir = "/path/to/freesurfer/subjects_dir/"
>>> subject_id = "42"
>>> bp = Brainprint(subjects_dir=subjects_dir, asymmetry=True, keep_eigenvectors=True)
>>> results = bp.run(subject_id=subject_id)
>>> results
{"eigenvalues": PosixPath("/path/to/freesurfer/subjects_dir/subject_id/brainprint/subject_id.brainprint.csv"), "eigenvectors": PosixPath("/path/to/freesurfer/subjects_dir/subject_id/brainprint/eigenvectors"), "distances": PosixPath("/path/to/freesurfer/subjects_dir/subject_id/brainprint/subject_id.brainprint.asymmetry.csv")}
Output
The script will create an output directory that contains a CSV table with
values (in that order) for the area, volume, and first n eigenvalues per each
FreeSurfer structure. An additional output file will be created if the
asymmetry calculation is performed and/or for the eigenvectors (CLI --evecs
flag or keep_eigenvectors
on class initialization).
Changes
There are some changes in functionality in comparison to the original BrainPrint scripts:
- currently no support for tetrahedral meshes
- currently no support for analyses of cortical parcellation or label files
- no more Python 2.x compatibility
References
If you use this software for a publication please cite:
[1] BrainPrint: a discriminative characterization of brain morphology. Wachinger C, Golland P, Kremen W, Fischl B, Reuter M. Neuroimage. 2015;109:232-48. http://dx.doi.org/10.1016/j.neuroimage.2015.01.032 http://www.ncbi.nlm.nih.gov/pubmed/25613439
[2] Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids. Reuter M, Wolter F-E, Peinecke N Computer-Aided Design. 2006;38:342-366. http://dx.doi.org/10.1016/j.cad.2005.10.011
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