Using BrainVISA

It is not the purpose of Brainstorm tutorials to teach you how to use BrainVISA. But many Brainstorm users are lost when it gets to the segmentation of the MRI. So here is a short introduction to the BrainVISA T1 MRI processing pipeline. To extract head and cortex meshes from a T1 MRI, you can also try to use: BrainSuite or FreeSurfer.

We are going to illustrate the use of BrainVISA with the MRI from the CTF tutorials. You should already have those files on your computer, if you followed the basic tutorials. If it is not the case, go to the Download page, and get the file sample_ctf.zip.

This tutorial was written for BrainVISA 4.3. To get started, or for additional information, you can also read the BrainVISA tutorial pages.

Installation

Running BrainVISA

Start Morphologist

The T1 MRI processing pipeline in BrainVISA is now called Morphologist. Double-click on the icon "Morphologist 2012" to get started.

morphologist.gif

The Morphologist window shows on the left the list of analysis steps that are part of this T1 MRI processing pipeline. They can be selected or unselected independently. When you click on a step, it shows all the possible options and input and output files on the right.

morphologist.gif

Select the MRI file

The only options than we need to set (hopefully), are the global ones, that you get when you click on the top element in the list (Morphologist 2012). Let's start with the selection of the MRI file:

Select the fiducial points

Other options

Keep all the other options to their default values. Just uncheck the steps: Cortical Fold Graph and Sulci recognition. We don't need those two, and they take a lot of time.
Click on Run and pray hard.

output.gif

What if if crashes?

Importing the results in Brainstorm

  1. Switch to the anatomy side of the database explorer
  2. Create a new subject, set the default anatomy option to "No, use individual anatomy"
  3. Right-click on the subject > Import FreeSurfer folder...

    import1.gif

  4. Select the top folder of your subject <subject_id> (/.../data/freesurfer/subjects/subject_id)

  5. 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).

    nVertices.gif

  6. 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.

    mriviewer.gif

  7. Place the six fiducials. If you need help, refer to this page: CoordinateSystems

  8. Click on Save to keep your modifications, and the automatic import will go on.
  9. The files that are imported from the subject_id folder are the following:
    • /mri/T1.mgz (T1 MRI volume)

    • /surf/lh.pial (grey/csf interface, left hemisphere)

    • /surf/rh.pial (grey/csf interface, right hemisphere)

    • /surf/lh.smoothwm (white matter, left hemisphere)

    • /surf/rh.smoothwm (white matter, right hemisphere)

    • /label/lh.*.annot (atlases: left hemisphere)

    • /label/rh.*.annot (atlases: right hemisphere)

  10. The successive steps that are performed automatically by Brainstorm:
    • Import all the surfaces (left/right, white/pial)
    • Load all the atlases available for each surface (note that the .pial and .smoothwm surfaces are matching point-to-point, so the same annotation files are imported for both surface types)
    • Downsample each hemisphere to the number specified in the options (by default 7500, half of the total default number 15000)
    • Merge left and right hemispheres for the two surface types: white matter and cortex envelope
    • Delete all the unnecessary surfaces
    • Generate a head surface from the MRI (this is not done by FreeSurfer)

  11. The files you can see in the database explorer in the end:

    checkDb.gif

    • MGH MRI: The T1 MRI of the subject, imported from the MGH file format (.mgz)

    • head mask (10000,0,2): Scalp surface generated by Brainstorm. The numbers indicate the parameters that were used automatically for this head: vertices=10000, erode factor=0, fill holes=2 (those are detailed later)

    • cortex_300000V: High-resolution cortex surface that was generated by FreeSurfer, that contains usually between 200,000 and 300,000 vertices.This one appears in green, it means that is going to be used as the default by the processes that require a cortex surface.

    • cortex_15000V: Low-resolution cortex surface, downsampled using the reducepatch function from Matlab (it keeps a meaningful subset of vertices from the original surface).

    • white_300000V: High-resolution white matter envelope from FreeSurfer

    • white_15000V: Low-resolution white matter, processed with reducepatch

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

    [ATTACH]

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...

checkAlign.gif

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:
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 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.

checkAlignMeg.gif

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:

Have fun...

Tutorials/SegBrainVisa (last edited 2012-12-18 22:48:41 by agrippa)