MRI segmentation with CIVET

The CIVET pipeline can be used to extract the cortical envelope from a T1 MRI. The process is fully automatic and the results can be imported in Brainstorm with just a few mouse clicks.

For more information, visit the CIVET website.

Running CIVET

CIVET is currently not available for download. It is available via the CBRAIN interface, linking high-performance computing (HPC) facilities across Canada and across the world. CBRAIN provides a web-based interface for configuring and running CIVET on large datasets. Subscription to external users is made possible via collaborative projects.

For detailed instructions on how to run CIVET: visit the CIVET website.

Importing the results in Brainstorm

Switch to the anatomy side of the database explorer
Create a new subject, set the default anatomy option to "No, use individual anatomy"
Right-click on the subject > Import anatomy folder...
Select the file format "!CIVET folder" and select the top folder of your subject <subject_id> (/.../data/freesurfer/subjects/subject_id)
To import the cortical thickness maps at the same time, you can select the format "!CIVET folder + Thickness maps" instead.
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).
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.
Place the six fiducials. If you need help, refer to this page: CoordinateSystems
Click on Save to keep your modifications, and the automatic import will go on.
The files that are imported from the subject_id folder are the following:
- /final/prefix_dsid_t1_final.mnc (T1 MRI volume)
- /surfaces/*_gray_surface_left_*.obj (grey/csf interface, left hemisphere)
- /surfaces/*_gray_surface_right_*.obj (grey/csf interface, right hemisphere)
- /surfaces/*_white_surface_left_*.obj (white matter, left hemisphere)
- /surfaces/*_white_surface_right_*.obj (white matter, right hemisphere)
- /surfaces/*_mid_surface_left_*.obj (mid-surface, left hemisphere)
- /surfaces/*_mid_surface_right_*.obj (mid-surface, right hemisphere)
- /thickness/*_native_rms_tlink_30mm_*.txt (cortical thickness map, left/right)
The successive steps that are performed automatically by Brainstorm:
- Import all the surfaces (left/right, white/pial/mid)
- 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, mid-surface and cortex envelope
- Delete all the unnecessary surfaces
- Generate a head surface from the MRI
- Read the cortical thickness maps
The files you can see in the database explorer at the end:
- MRI: The T1 MRI of the subject, imported from the MINC file format (.mnc)
- 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)
- mid_80000V: High-resolution mid-surface surface that was generated by !CIVET (intermediate between the pial and the white surfaces)
- mid_15000V: Low-resolution mid-surface surface, downsampled using the reducepatch function from Matlab (it keeps a meaningful subset of vertices from the original surface). It appears in green in the database explorer, ie. it is going to be used as the default by the processes that require a cortex surface.
- cortex_300000V: High-resolution pial surface from !CIVET
- cortex_15000V: Low-resolution pial surface, processed with reducepatch
- white_300000V: High-resolution white matter envelope from !CIVET
- white_15000V: Low-resolution white matter, processed with reducepatch
- CIVET/natine_rms_tlink_30mm: Cortical thickness maps
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.

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...

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 or BrainSuite.

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.

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)

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:
http://freesurfer.net/fswiki/CorticalParcellation

With FreeSurfer 5.3, 4 atlases are available on all the individual brains:

Destrieux atlas (?h.aparc.a2009s.annot): more information
Desikan-Killiany atlas (?h.aparc.annot): more information
Mindboggle (?h.aparc.DKTatlas40.annot): more information
Brodman areas (?h.BA.annot and ?h.BA.thresh.annot): more information

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'.

To access them from the interface: Double-click on the cortex and go to the Scout tab, and click on the drop-down list to select another Atlas (ie group of scouts):

Desikan-Killiany atlas

Displayed respectively in: FreeSurfer, Brainstorm (high-resolution) and Brainstorm (15000 vertices)

Destrieux atlas

Displayed in Brainstorm with the original scouts colors (left) or classified in 6 regions (right): pre-frontal, frontal, central, parietal, temporal, occipital, occipital. You can switch between the two views with the button "Identify regions with colors" in the toolbar on the right of the scouts list.

Subcortical structures: aseg atlas

The file aseg.mgz contains a volume atlas of 40 subcortical regions. Brainstorm reads those volume labels and tesselates some of those regions, groups all the meshes in a large surface file where the regions are identified in an atlas called "Structures". It identifies: 8 bialateral structures (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, cerebellum) and 1 central structure (brainstem).

You can easily extract one structure (for example the brainstem or the cerebellum) by selecting the corresponding entries in the scouts list and selecting the menu Scout > Edit surface > Keep only selected scouts. It creates a new surface with only the selected regions. If you want to remove one or several structures, use the menu "Remove selected scouts" instead.

Read more about the FreeSurfer subcortical atlas on the software wiki:
http://ftp.nmr.mgh.harvard.edu/fswiki/SubcorticalSegmentation

Registered sphere

The registered sphere is saved in each surface file in the field Reg.Sphere.Vertices. There is nothing that can be done with this information at this point, but it will become helpful when projecting the source results from the individual brains to the default anatomy of the protocol, for a group analysis of the results.

Read more about the FreeSurfer registration process on the software wiki:
https://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceRegAndTemplates

Cortical thickness

The cortical thickness can be saved as a cortical map in the database (a "results" file). This result is generated when using the file format "FreeSurfer folder + Thickness maps" in the Import anatomy folder selection.

FSAverage template

Instead of the MNI Colin27 brain, you can you the FreeSurfer average subject "FSAverage" as your default anatomy in Brainstorm. This template is an average of 40 subjects using a spherical averaging described in (Fischl et al. 1999).

To change the default, right-click on "(Default anatomy)" > Use template > FSAverage. If it is not available on your computer yet, it will be downloaded automatically from the server to your user folder: $HOME/.brainstorm/templates/anatomy.

If you are using the FSAverage template but not a regular user of FreeSurfer, please register on their website: registration page.

Running the folder import as a process

You can import the FreeSurfer folders from scripts, but you have to provide manually the position for all the fiducial points: process Import anatomy > Import anatomy folder.

The corresponding process function is: brainstorm3/toolbox/process/functions/process_import_freesurfer.m

Manual import of the anatomy

In case you need to import the MRI, surfaces and atlases separately instead of using the menu "Import anatomy folder", here is the sequence of operations to perform to get to the same result:

From the Anatomy side of the database explorer: create a subject.
Right-click on the subject folder > Import MRI > Select "mri/T1.mgz"
Set the 6 fiducial points, save
Right-click on the subject folder > Import surfaces > Select the FreeSurfer file format > Select simultaneously from the "surf" folder: lh.pial, lh.white, rh.pial, rh.white
Double-click on lh.pial toi display it. In the scout tab: Atlas > Load atlas > select all the lh.*.annot files available in the label folder. Close the figure.
Repeat for the other surfaces: lh.white, rh.pial, rh.white
Right-click on lh.pial > MRI registration > Load FreeSurfer sphere > Select "surf/lh.sphere.reg"
Repeat with the other surfaces (use rh.sphere.reg for the right hemisphere, white and pial surfaces)
Select all the surfaces, right-click > Less vertices > 7500 vertices > Select the first option "Matlab reducepatch"
Select lh.pial, rh.pial, right-click > Merge surfaces: Generates a surface cortex_250000V
Select lh.white, rh.white, right-click > Merge surfaces: Generates a surface white_250000V
Select lh.pial_7500V, rh.pial_7500V, right-click > Merge surfaces: Generates a surface cortex_15000V
Select lh.white_7500V, rh.white_7500V, right-click > Merge surfaces: Generates a surface white_15000V
Delete all the separate hemispheres: ?h.pial, ?h.white
Double-click on cortex_15000V to set it as the default cortex
Right-click on the subject folder > Import surfaces > Select the file format "Volume mask of atlas" > Select the file mri/aseg.mgz
Go to the functional view of the protocol, create a condition "FreeSurfer". Leave your mouse for a second over the new folder, an note the study index (iStudy).
From the Matlab command window, you can import the thickness maps with the following call:
- ThickFile = import_sources(iStudy, CortexHiFile, ThickLhFile, ThickRhFile, 'FS');
- CortexHiFile = full path to the high-res cortex file (right-click > File > Copy file path to clipboard)
- ThickLhFile = full path to the surf/lh.thickness file
- ThickRhFile = full path to the surf/rh.thickness file

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