Hi FreeSurfers,
Due to an accident and after several hundreds of hours of work I was finally
able to completely (actually not completely, but it seems to work) process
high resolution data with an isometric voxel size of 0.6mm without any
manual intervention, while using the advantage of all atlases. I would like
to share my experience with you and especially would like to know if and how
some of my individual changes to the recon-all stream may affect the
results.
The data I used was acquired at 7T (Siemens), so my volumes were not very
homogenous. To get rid of most of the inhomogeneities we are using a method
at our lab in which two volumes are acquired, a MPRAGE and 3D gradient echo.
Both volumes are co-registered and afterwards the MPRAGE is divided by the
3D GE. Everything further has been done directly using FreeSurfer.
First you need to run recon-all autorecon1 cm noskullstrip s <your
subject>. Using the cm flag the volumes are not conformed to 1mm^3 voxel
size and 256^3, but to the smallest voxel size (in my case 0.5990mm^3 and
385^3). It is crucial to not run skullstrip using the high resolution data
as this will not work! You need to go to your subject/mri folder and use
mri_convert cs 1 nu.mgz nu.conformed.mgz, this creates a conformed version
of the nu.mgz. Now you should run mri_em_register skull nu.conformed.mgz
$FREESURFER_HOME/average/RB_all_withskull_2008-03-26.gca
transforms/talairach_with_skull.lta.
This has to be done using a conformed nu.mgz as in the following stage
mri_watershed seems to conform the input file (Will it be really conformed?
The output volume doesnt suggest this.) and if the talairach_with_skull.lta
is created using a not conformed volume one gets an error stating that the
WM intensity is lower than CSF intensity and the stage is exited. The
nu.conformed.mgz is only used during this stage, so your high resolution
volumes will never (Never? At least the output volumes are not.) be
resampled, conformed or whatever to a lower resolution.
After this has been done, one can use recon-all skullstrip s <your
subject> and take advantage of the atlas! Though the input volume (T1.mgz)
seems to be conformed during mri_watershed, the output volume
(brainmask.mgz) will have the correct resolution. If the brainmask.mgz
doesnt look well, try adding the wsatlas switch first, as this improved
the skull stripping if only really small bits of skull and dura were still
left or small pieces of the temporal lobe or cerebellum were cut off. If
this doesnt help much adjust the watershed threshold using the wsthresh
<value> switch (but still use wsatlas) like described in the wiki.
Now run recon-all gcareg canorm careg careginv rmneck skull-lta
calabel s <your subject>. Even though the aseg.mgz should look perfectly
fine, one needs to stop here, as the normalization2 stage can be run only
if the aseg.mgz is conformed (Why does it need to be conformed?). This is
something you dont want, so go to the subject/mri folder again and run
mri_normalize mask brainmask.mgz norm.mgz brain.mgz.
Right now I'm running the missing stages of -autorecon2 (being at the -fix
stage which will take some time) and I think it should work totally fine.
Maybe the following stages using the aseg.mgz might not run as those maybe
want the aseg.mgz to be conformed as well, but I don't know yet.
Additionally in my case this wouldn't be a problem as I just want to measure
the cortical thickness.
I would highly appreciate if you could answer the questions in the brackets
and how the results might be effected by the changes I have done.
By the way, I tried running mri_nu_correct.mni using the T1.mgz as the input
volume and running mri_normalize again afterwards to improve the
inhomogeneity correction. The result looks very good, but parts of the skull
and dura are not erased during the skull stripping stage (as they seem to
match the intensities of GM and WM). If I adjust the watershed threshold so
these are erased, pieces of the cerebellum and temporal lobes are erased
additionally. Would it be possible to run mri_nu_correct using the
brainmask.mgz as input volume and mri_normalize afterwards, so the
inhomogeneity correction can be further improved? Will mri_nu_correct.mni
work fine on a volume without skull?
Thanks in advance,
Regards,
Falk