Welcome to the BrainSuite Website
BrainSuite is a collection of open source software tools that enable largely automated processing of magnetic resonance images (MRI) of the human brain. The major functionality of these tools is to extract and parameterize the inner and outer surfaces of the cerebral cortex, to segment and label gray and white matter structures, and to analyze diffusion imaging data. BrainSuite also provides several tools for visualizing and interacting with the data.
We are pleased to announce the release of BrainSuite version 19a. BrainSuite19a includes many recently added features, including automated parameter tuning for skull-stripping and new diffusion modeling tools.
BrainSuite19a now available
The latest version of BrainSuite (v.19a) is available for download. This release features:
- New automated skull-stripping parameter tuning
- GUI for Windows, Mac OSX, and Linux platforms
- Command line tools for performing cortical surface extraction, surface/volume registration, and processing of diffusion weighted images
- Ability to create and use custom brain atlases.
- Source code (C++ and Matlab) is provided under a GPLv2 license (see http://brainsuite.org/building/ for build instructions)
- Compiled MATLAB code now uses MATLAB R2015b Matlab Compiler Runtime, which provides improved compatibility with more recent versions of Mac OS X.
BrainSuite User Interface
BrainSuite provides an easy-to-use interface for performing data processing, analysis, and visualization of brain MRI data. The GUI is available for Mac, Windows, and Linux.
Cortical Surface Extraction
BrainSuite provides a flexible set of tools for performing rapid automated extraction of cortical surface models.
Surface-constrained Volumetric Registration
BrainSuite uses the novel Surface-constrained Volumetric Registration (SVReg) to align subject MRI to a labeled atlas.
BrainSuite Diffusion Pipeline
The BrainSuite Diffusion Pipeline (BDP) provides a set of tools for processing diffusion weighted MRI (dMRI). This functionality includes:
- Correction of geometric distortion in EPI data using a T1-weighted structural as an anatomical reference
- Tensor fitting and estimation of diffusion parameters aligned with the T1-weighted MRI.
- Orientation distribution function (ODF) estimation using FRT, FRACT, and 3D-SHORE