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Dear Colleagues
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Hello Freesurfer Experts,
I am trying to compare the left and right hemisphere of a group of PD patients
with Mass-Univarate LME.
>From what I can see in the wiki tutorial, the mris_preproc only assembles data
>from one hemisphere at a time, which
Hi Montse – In case you’re still having trouble with this subject, I would
check the structural segmentation (aparc+aseg from recon-all) and see if
there’s anything wrong in parts of the brain that the ATR goes through. If that
looks fine, then sending along the entire trac-all.log file would
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Hello Freesurfer Developers,
I'm attempting to use Univariate LME analysis to compare the symptomatic and
asymptomatic hemispheres of early stage Parkinson's disease patients.
I re-organized the data so that the symptomatic hemisphere is the left
The output of TRACULA is a probability distribution that tells you how likely
each voxel is to be part of the tract that you’re looking at. Voxels with low
probability values are not very likely to be part of the tract. Setting the
threshold in freeview to 20% means that you only want to
Hi Loic – In simple terms, motion will cause a rigid transformation of the
brain (translation and rotation only), whereas eddy currents will add non-rigid
effects (scaling/stretching). By registering each DWI to the first b=0 image,
and then extracting the translation and rotation part of the
Hi Tim – The best method to use will depend on the data you have. If you have
very high b-values, you should use eddy. You can turn off the eddy current part
of the preprocessing with “set eddy=0” in the config file, and run trac-all on
your corrected images.
Best,
a.y
From:
This is not entirely surprising. You have a b-value that’s quite high (b=3000)
and eddy_correct will not work well with such high b-values, because is tries
to register the b=3000 images to a b=0 image, and the b=3000 images do not have
enough anatomical detail to be registered correctly. You
