The Lead Toolbox is a MATLAB-based toolbox with several subparts that work ideally together. Lead-DBS is a toolbox that allows the user to localize and visualize in a 3D model electrodes in patients treated with deep brain stimulation. Lead-Connectome is a toolbox entailed with functional and structural whole-brain connectome analyses.
This manual focuses on the Lead-DBS subpart of the toolbox.
Linear and nonlinear normalization of MRI and CT images to MNI space
Reconstruction of the electrode trajectories
Manual correction of the electrode localization
Visualization of results in 2D slice views
Visualization of a 3D model showing DBS electrodes and their target areas
Calculation of the Volume of Activated Tissue (VAT) and visualization of the structural connectivity from the VAT to other brain areas
Lead-DBS can be seen as a collection of useful tools that have been gathered together for the purpose of DBS electrode reconstructions and related processing. The core job of our development team is to find and plug in the best neuroimaging tools available within the open-source community and write bits of pieces of own code where no good code can be found. 3D-visualizations and electrode reconstruction algorithms (TRAC/CORE) have been built by ourselves. As for other parts of the toolbox, we aim at incorporating the best tools available. For instance, normalizations into MNI space can be done from within Lead-DBS by either DARTEL or ANTs, both of which have shown superior to all 12 competing algorithms in Klein 2009. As for Fibertracking, Lead-DBS among other routines uses the Gibbs' tracking algorithm, which showed superior to all 9 competing algorithms in Fillard 2011. Thus, Lead-DBS heavily depends on shared libraries and other tools that should be referenced properly if used for research projects. Please find a list of tools used by Lead-DBS here.