= T1-MRI Segmentation with BrainSuite =
You can use the free BrainSuite and SVReg software package to extract segmented brain surfaces from a T1-weighted MRI image. Surface extraction and segmentation can either be automatic or manual--this tutorial will step you through the automated process (more information on manual tweaks can be found in [[http://brainsuite.loni.ucla.edu/processing/|BrainSuite's documentation]]).

For this tutorial, we will use the 01.nii file from the CTF tutorials. If you do not already have those files on your computer, you can go to the [[http://neuroimage.usc.edu/brainstorm3_register/download.php|Download page]] and get the sample_ctf.zip file. After extracting the zip file, the MRI image we will be using can be found in the Anatomy folder.

Unlike BrainStorm, Freesurfer, and BrainVisa, BrainSuite does not use a database structure for storing subject information and scans. Instead, by default it stores its output in the same folder as the input MRI scan. Thus, it is often best to have each subject's structural scan in its own folder.

To extract head and cortex meshes from a T1 MRI, you can also try to use: [[Tutorials/SegBrainVisa|BrainVISA]] or [[Tutorials/SegFreeSurfer|FreeSurfer]].

== Installation ==
 1. Download the latest version of BrainSuite from http://www.loni.ucla.edu/Software/BrainSuite13.

 1. Install it on your computer by following the instructions in [[http://brainsuite.loni.ucla.edu/quickstart/installation/|BrainSuite's quick start installation guide]]. Note that you will be using Surface/Volume Registration (SVReg) to do the surface segmentation, so you will need to follow the instructions in the pink box on the top of the page to download a compatible MATLAB Compiler Runtime. You may ignore any instructions about "Setting up BDP" if you are not planning on using BrainSuite for diffusion imaging.

 1. Start BrainSuite (if it is not already open following installation).

== Running BrainSuite ==
 1. Open the T1-weighted scan in BrainSuite by going to File > Open Volume... and navigating to the CTF tutorial's 01.nii scan.

 1. Check that the scan is in the correct orientation. Some of the modules BrainSuite and SVReg run while processing a scan assume that the scan is in LPI coordinates. Practically, this means the screen should look like below when you open it.

 1. Open the Cortical Surface Extraction sequence dialog by clicking on Cortex > Cortical Surface Extraction Sequence

 1. Check the box next to "Register and label brain".
 1. At the bottom of the dialog window, check that the filename prefix is "01" and that the working directory is the Anatomy folder of the CTF tutorial files (or, if you moved the scan to its own folder, that folder)
 1. Click "Run All". The full surface creation and segmentation process should take about 1 - 1.5 hours, depending on your machine.

== Importing the results in Brainstorm ==
 1. Switch to the anatomy side of the database explorer
 1. Create a new subject, set the default anatomy option to "No, use individual anatomy"
 1. Right-click on the subject > Import BrainSuite folder...

 1. Select the top folder of your subject (i.e. the "Working Directory" from BrainSuite)

 1. Then you're prompted for the number of vertices you want in the final cortex surface. This will by extension define the number of dipoles to estimate during the source estimation process. By default we set this value to 15000 for the entire brain (it means 7500 for each hemisphere).
 1. The MRI Viewer appears, and a help window asks you to validate the orientation of the MRI and to define the 6 fiducial points. If something doesn't look right at this step, for instance if the MRI is not presented with a correct orientation, you should stop this automatic import process and follow the manual instructions in the basic tutorial pages.
 1. Place the six fiducials. If you need help, refer to this page: [[http://neuroimage.usc.edu/brainstorm/CoordinateSystems|CoordinateSystems]]

 1. Click on Save to keep your modifications, and the automatic import will go on.
 1. The files that are imported from the BrainSuite folder are the following:
  * '''01.nii''' (original T1 MRI volume)

  * '''01.scalp.dfs''' (head surface)

  * '''01.inner_skull.dfs''' (inner skull surface)

  * '''01.outer_skull.dfs''' (outer skull surface)

  * '''01.left.pial.cortex.svreg.dfs''' (grey/csf interface, left hemisphere)

  * '''01.right.pial.cortex.svreg.dfs''' (grey/csf interface, right hemisphere)

  * '''01.left.inner.cortex.svreg.dfs''' (white matter, left hemisphere)

  * '''01.right.inner.cortex.svreg.dfs''' (white matter, right hemisphere)

  * '''brainsuite_labeldescription.xml''' (not imported, but required for properly labelling scouts)

 1. The successive steps that are performed automatically by Brainstorm:
  * Import all the surfaces (head, skull, left/right, white/pial)
  * Read the anatomical label information from pial and white matter surfaces
  * Downsample each hemisphere to the number specified in the options (by default 7500, half of the total default number 15000)
  * Merge left and right hemipsheres for the two cortical surface types: white matter and cortex envelope
  * Downsample the head and skull surfaces
  * Delete all the uncessary surfaces

 1. The files you can see in the database explorer at the end:
  * '''MRI''': The T1 MRI of the subject

  * '''01.scalp_1082V''': The head surface (downsampled to 1082 vertices)

  * '''01.outer_skull_642''': The skull surface (downsampled to 642 vertices)

  * '''01.inner_skull_642''': The inner skull surface (downsampled to 642 vertices)

  * '''cortex_270604V''': High-resolution cortical surface that was generated by BrainSuite.

  * '''cortex_15000V''': Low-resolution cortical surface, downsampled using the '''reducepatch''' function from Matlab (it keeps a meaningful subset of vertices from the original surface). This one appears in green, meaning that it is going to be used as the default by the processes that require a cortex surface.)

 1. A figure is automatically shown at the end of the process, to check visually that the low-resolution cortex and head surfaces were properly imported. If it doesn't look like the following picture, do not go any further in your source analysis, fix the anatomy first.

== Handling errors ==
==== How to check the quality of the result ====
It's hard to estimate what would be a good cortical reconstruction. What you are trying to spot at this level is mostly the obvious errors, like when the early stages of the brain extraction didn't perform well, just with a visual inspection. Play with the ''Smooth'' slider in the ''Surface ''tab. If it looks like a brain (two separate hemispheres) in both smooth and original views, it is probably ok.

Display the cortex surface on top of the MRI slices, to make sure that they are well aligned, that the surface follows well the folds, and that left and right were not flipped: right-click on the low-resolution cortex > MRI registration > Check MRI/surface registration...

[[attachment:alignmrisurface.png]]

==== The cortex looks bad ====
It is critical to get a good cortex surface for source estimation. If the final cortex surface looks bad, it means that something didn't work well somewhere along the !FreeSurfer pipeline. You can refer to the following page to fix the problems manually:<<BR>>http://surfer.nmr.mgh.harvard.edu/fswiki/RecommendedReconstruction

If after following those instructions you still don't manage to get good surfaces, you can try to run the [[Tutorials/SegBrainVisa|automatic MRI segmentation from BrainVISA]].

==== The head surface looks bad ====
It is not mandatory to have a perfect head surface to use any of the Brainstorm features: you don't necessarily have to recognize the face (for the anonymity of the figures, it can be even better if you don't).

The head surface is important mostly for the alignment of the MEG sensors and the MRI. If you digitized the head shape with a Polhemus device, you can align automatically the head surface (hence the MRI) with the MEG sensors (in the same referential as the Polhemus points). The quality of this automatic registrations depends on the quality of both surfaces: the Polhemus head shape (green points) and the head surface from the MRI (grey surface). If you placed lots of points on the nose but your head surface doesn't have a nose, those points are not going to help. Except for that, a nice head shape is mainly useful for producing nicer figures.

{{attachment:checkAlignMeg.gif||height="243",width="298"}}

If the default head surface looks bad, you can try generating another one: right-click on the subject folder > Generate head surface. The options are:

 * '''Number of vertices''': Number of points that are kept from the initial isosurface computed from the MRI. Increasing this number may increase the quality of the final surface.

 * '''Erode factor''': Number of pixels to erode after the first binary threshold of the MRI. Increasing this number removes small components that are connected to the head.

 * '''Fill holes factor''': Number of dimensions in which the holes should be identified and closed. Increasing this number removes more of the cavities of the head surface (0=no correction, 1=removes holes inside the surface, 3=closes all the features that make the surface non-convex)
  . {{attachment:generateHead.gif}}

== Cortical parcellations ==
The default analysis pipeline in !FreeSurfer  implements an automatic parcellation of the cortical surface in  anatomical regions. The description of this feature is available here:<<BR>>http://freesurfer.net/fswiki/CorticalParcellation

Those atlases are imported in Brainstorm as scouts  (cortical regions of interest), and saved directly in the surface files.  To check where they are saved: right-click on the low-resolution cortex  file > File > View .mat file. You can see that 4 structures  "Atlas" are available, the first one that has Name='User scouts', and  the second one Name='Destrieux'.<<BR>><<BR>>

{{attachment:viewMat.gif}} <<BR>><<BR>>

To access them from the interface:

 1. Double-click on the low-resolution cortex (works with the high-resolution too, it's just longer to display)
 1. Go to the ''Scout'' tab, and click on the drop-down list to select another ''Atlas ''(ie group of scouts):
  * Destrieux atlas (*.aparc.a2009s.annot)
  * Desikan-Killiany atlas (*.aparc.annot)
  * Some Brodman areas (*.BA.annot)

{{attachment:scoutTab.gif}}

== Feedback ==
<<EmbedContent(http://neuroimage.usc.edu/brainstorm3_register/get_feedback.php?Tutorials/LabelFreeSurfer)>>