## page was renamed from brainsuiteBDP
## page was renamed from brainsuite
= FEM tensors estimation with BrainSuite =
''Authors: [[https://neuroimage.usc.edu/brainstorm/AboutUs/tmedani|Takfarinas Medani]], Francois Tadel, Anand Joshi and Richard Leahy''

'''[TUTORIAL UNDER WRITING: NOT READY FOR PUBLIC USE]'''

Describe brainsuite here : here we will describe the process of the brain tissues anisotrpy estimation and the different functions that brainstorm offers.

This tutorial explains how to use Brainsuite to estimate the anisotropy of the brain tissues.

refer to this page

[[https://neuroimage.usc.edu/brainstorm/Tutorials/SegBrainSuite?highlight=(Anand)|https://neuroimage.usc.edu/brainstorm/Tutorials/SegBrainSuite?highlight=%28anand%29]]

The realistic tensors are estimated from the Diffusion-Weighted Images (DWI). For this purpose, Brainstorm calls internally the BrainSuite Diffusion Pipeline to compute the diffusion tensors on each brain voxel. Afterward, the Effective Medium Approach is applied to convert the diffusion tensors to the conductivity tensors. The following section shows the users how to do it from the graphical interface.

Only the NIfTI is supported. All the diffusion data, including the DWI file and direction and the value of the gradient files, respectively the *.nii, the *.bval and the *.bvec are required. Ideally, these files should have the same name and saved in the same folder.

<<TableOfContents(2,2)>>

== Requirement ==
 * You have already followed all the introduction tutorials
 * You have a working copy of Brainstorm installed on your computer

== Brainsuite Installation ==
 1. Download the latest version of BrainSuite from http://www.brainsuite.org/download.
 1. Install it on your computer by following the instructions in [[http://brainsuite.bmap.ucla.edu/quickstart/installation/|BrainSuite's quick start installation guide]].
 1. Note that you will be using BrainSuite Diffusion Pipeline(BDP), so you need to install a compatible [[http://www.mathworks.com/products/compiler/mcr|MATLAB Compiler Runtime]](last version).
 1. Start BrainSuite to check if the installation (It's not required to open BrainSuite to run this tutorial).
 1. The BrainSuite installation folder should be informed in the Brainstorm preferences

{{https://user-images.githubusercontent.com/6920058/81406567-1c785400-913a-11ea-9048-28c7459af7da.png|image}}

== Dataset ==
In this tutorial, we use the Brainsuite dataset example available on the Brainsuite tutorial webpage

http://brainsuite.org/tutorials/. The T1w of the subject can be download from this link  [[http://brainsuite.org/WebTutorialData/BrainSuiteTutorialSVReg_Sept16.zip|BrainSuiteTutorialSVReg_Sept16.zip]]. The DWI from this link  [[http://brainsuite.org/WebTutorialData/DWI_Feb15.zip|DWI_Feb15.zip]]

The first link contains the T1 MRI, with the name '2523412.nii.gz'. as in this figure,

{{attachment:vierMriFolder.JPG||height="130",width="580"}}

The second file is the DWI and should contain at least three files

{{attachment:vierDWIFolder.JPG||height="150",width="580"}}

Where the *.bval is a text file that contains the value of the gradient, and the *.bvec is also a text file that contains the orientation of the gradient. The nii.gz file is the NifTi file of the DWI where the images are stored.

== Realistic condctivity tensors ==
First, you need to create a new subject in your protocol, let call it the 'BrainSuiteSubject'. Then import the T1 MRI of the subject and set the fiducials points as explained in the previous tutorial.

{{attachment:mri.JPG||height="100",width="250"}}

=== Diffusion tensor generation (DTI) from DWI ===
Right-click on the subject and then select the item "Convert DWI to DTI".

Then follow the popup windows by selecting the DWI, bval and bval. If these files are in the same folder, Brainstorm will detect them automatically, otherwise the user will be asked to browse the files one by one (as it's the case in this tutorial).

In this step, Brainstorm calls the Brainsuite internally, and the diffusion tensors are computed. At the end of this process, a new node will appear in the Brainstorm database with the name 'DTI-EIT'. This name refers to, DTI: diffusion tensors images, and EIG for eigenvalue, since the eigenvalues and eigenvectors are computed at voxel and stored in Brainstorm database.

{{attachment:mriAndDTI-EIG.JPG||height="100",width="250"}}

=== Conductivity tensor generation from DTI ===
The Effective Medium Approach is applied to convert the diffusion tensors to the conductivity tensors. This step requires the FEM mesh of the head model. You can generate the FEM head model from the MRI as explained on this page (add link).
 
For the following, we used the SimNibs FEM mesh generation. The following figure shows the FEM mesh obtained from using the T1 MRI. Note that this mesh is obtained only from the T1, the use of the T2 is highly recommended if it's available. 


The FEM head model to use for tensors should be selected and highlighted with the green color (double click on the FEM mesh node to select it)

When this is done, then right-click on the subject > Convert DWI to DTI,

Brainstorm will load the avialbale tissue in the FEM head model and the following windows appears.

Select the WM anisotropy and kee all the oher tissues as isotropic.

The process of conversion from DWI to Conductivity tensors use the EMA, furthermore, brainstorm propose the option to use the adaptative EMA with the volume constraint option [ref]. In this example we select the EMA with the VC.

The process will take around 10 min, and then the FEM tensors are computed and stored in the FEM strucutre. [explain how it is organised and how to use it outside brainstorm ]

=== Display the tensors ===
== Artificial/simulated conductivity tensors ==
In the case where the DWI is not available, or the users desire to evaluates the effect of the conductivity change on the model, the artificial conductivity can be use.

Two approaches are integrated within Brainstorm. Either the

== References ==