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'''Question:''' After running recon-all which volumes/surfaces should be checked? During the tutorial we focused on wm and pial edits; however, it was not clear how to utilize the surface reconstructions/inflations, etc. and at what point in the data checking each of these volumes/surfaces should be referenced. We also only monitored the data from a coronal view. Do you suggest also making edits on sagittal/axial views as well? Should you only work on one view at a time?

Answer: You would typically view brainmask.mgz, wm.mgz, and aseg.mgz to check & fix recons. Brainmask is used to correct pial errors. wm is used to fix most white surface errors. Control points can be placed using the brainmask as a guide to fix white surface errors caused by intensity normalization problems.

The inflated surface can be useful for looking for obvious errors (holes in the surface or extra bumps on the surface), however, not all errors will be obvious on the inflated surface AND not all bumps on the surface need to be fixed. Thus, looking at the inflated surface when you are just getting started or have a recurring problem that shows up on the surface could be useful. But it could also take up a lot of time, especially if data quality is poor and the entire surface will look bumpy.

The error should be fixed completely. In other words, the error should not be visible in any view. However, you should edit in whichever view you feel most comfortable with and check the other views to be sure you got everything.


This wiki page contains the students questions and answers from the November 2013 Freesurfer course.

Question List


Answers to May 2014 Course questions:

Topic: Gray Matter Volume
Question: In v5.0 and above, there is a stat within each subject's stat folder that is a single value for whole brain gray matter volume. Two questions regarding that metric: 1) Does that include the cerebellum? 2) Is there a way to access that statistic using version 4.5?

Answer: 1) yes 2) The easiest way to do this is to download version 5.3 and just run the program to generate the stats files, eg

cd $SUBJECTS_DIR/subject

mri_segstats --seg mri/aseg.mgz --sum stats/aseg.53.stats --pv mri/norm.mgz --empty --brainmask mri/brainmask.mgz --brain-vol-from-seg --excludeid 0 --excl-ctxgmwm --supratent --subcortgray --in mri/norm.mgz --in-intensity-name norm --in-intensity-units MR --etiv --surf-wm-vol --surf-ctx-vol --totalgray --euler --ctab $FREESURFER_HOME/ASegStatsLUT.txt --subject subjects

The data will be in stats/aseg.53.stats
Doug Greve

Topic: Control points
Question: I use control points followed by autorecon to include areas that are obviously part of the brain but were not included in the first run. how many times should i do this, because sometimes i do it like 8 or 10 times (with added control points) and that area is still excluded, is there another way of doing this?

Answer: There are a couple of possibilities. Have you checked the wm.mgz to make sure that is filled in for every voxel you think is white matter? If not, fill that in and try rerunning (possibly without the control points).

Also, if control points are not placed on voxels that are less than 110, then you might not see the desired effect. It could also be that you are not placing enough control points on enough slices.

Without seeing your case, I can't say for sure what you need but most cases need 3-4 control points on every other slice for several slices. Since control points are used for fixing intensity problems, you'll need to place them on most of the slices that have low intensity in that region and not necessarily just on the slices that have problems with the surface.

If control points were placed in gray matter, partial volumed voxels, or white matter bordering gray matter, that could be causing the problem. You should delete those control points.

If after trying the above, control points still don't seem to be working, let us know which version you are working with so we can investigate.
Allison

Question: I used AnatomicalROIFreeSurferColorLUT to determine my ROI, i then used FSL math get the volume of this ROI. I wanted to compare between Healthy control and patients, is it ok to publish my results using the above as a reliable method for volume assessment?

Answer: It is probably ok, though you do not need to do it this way. The recommended method is to get this information from the statistics files (eg, subject/stats/aseg.stats or lh.aparc.astats). These statistics are computed using partial volume correction and surface-based volume correction so they should be more accurate. -Doug Greve

Question: After running recon-all which volumes/surfaces should be checked? During the tutorial we focused on wm and pial edits; however, it was not clear how to utilize the surface reconstructions/inflations, etc. and at what point in the data checking each of these volumes/surfaces should be referenced. We also only monitored the data from a coronal view. Do you suggest also making edits on sagittal/axial views as well? Should you only work on one view at a time?

Answer: You would typically view brainmask.mgz, wm.mgz, and aseg.mgz to check & fix recons. Brainmask is used to correct pial errors. wm is used to fix most white surface errors. Control points can be placed using the brainmask as a guide to fix white surface errors caused by intensity normalization problems.

The inflated surface can be useful for looking for obvious errors (holes in the surface or extra bumps on the surface), however, not all errors will be obvious on the inflated surface AND not all bumps on the surface need to be fixed. Thus, looking at the inflated surface when you are just getting started or have a recurring problem that shows up on the surface could be useful. But it could also take up a lot of time, especially if data quality is poor and the entire surface will look bumpy.

The error should be fixed completely. In other words, the error should not be visible in any view. However, you should edit in whichever view you feel most comfortable with and check the other views to be sure you got everything.


Questions from previous courses:

Topic : 1.5 and 3T longitudinal data

Question: I have a set of longitudinal data that began on a 1.5T scanner but then our research group moved to a 3T scanner exclusively. Is it possible to use longitudinal analysis in FreeSurfer to analyze both 3T and 1.5T data in the same analysis or possibly smooth across both to accomplish this analysis?

Yes, you can add the scanner type as a time varying covariate into a linear mixed effects model. It would be good to have several time points before and after the change to get more reliable slope estimates on both sides. See also LinearMixedEffectsModels .

MartinReuter


Hello, I would like to know how to measure the cerebellar vermis volume using freesurfer. As far as I know, freesurfer provide cerebellum cortex volume and cerebellum white matter volume in the aseg.stats file, but I could not find cerebellar vermis volume. Can freesurfer provide cerebellar vermis volume? I found a web page in freesurfer wiki that describe cerebellum parcellation. http://surfer.nmr.mgh.harvard.edu/fswiki/CerebellumParcellation_Buckner2011 I hope to obtain the volume of each subregion of cerebellum, but I have not understood the procedure. I know the MNI152 atlas is in the $FREESURFER_HOME/average/ directory. Could you tell me how to warp the MNI152 parcellations to subjects' native structural MRI space and extract the volume of each subregion? Thanks in advance.

We do not segment the cerebellar vermis. If you want to measure it or label it, you will need to manually draw it on each of the subjects or if you find another atlas with the required label, register that to your subject and project the label to that space. The cited URL provides cerebellar clustering in the MNI152 nonlinear space. You need to use the talairach.m3z transformation to map the labels back to the subject's native space.


I know freesurfer can process cortical surface correctly for the subjects who are over 5 years old. How do you think the reliability of the freesurfer outputs in very young children (e.g. 3-4 years old).

Not good. We do not encourage people to use FS recon for that age group. We do not have a qunatifiable performance measure though.

FsTutorial/QuestionAnswers (last edited 2018-10-04 16:22:01 by AllisonStevens)