No. You can use mri_concat with --mtx option, where the argument to --mtx is an
asci matrix that is square and diagonal with the weighting factors on the
diagonal. You could also use mri_glmfix with the --X option, where X is an
ascii column matrix of weighting factors (make sure that the the sum.^2 = 1)
On 12/21/18 2:31 PM, Matthieu Vanhoutte wrote:
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Thanks Douglas.
Is there a way to compute a weighted average in one command with fscalc ?
Best,
Matthieu
Le mar. 18 déc. 2018 à 18:03, Greve, Douglas N.,Ph.D.
<dgr...@mgh.harvard.edu<mailto:dgr...@mgh.harvard.edu>> a écrit :
you can use mri_vol2surf to sample at different depths. If you want a simple
average across cortex, then you can use --projfrac-avg .35 .65 .05
If you want to do more sophisticated weighting, then you will have to sample at
each layer and then combine the files (eg, fscalc). Unless you have very small
voxels, it probably will not make a difference.
On 12/18/18 4:50 AM, Matthieu Vanhoutte wrote:
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Dear experts,
Is there any advice on this point ?
Best,
Matthieu
Le mer. 12 déc. 2018 à 10:47, Matthieu Vanhoutte
<matthieuvanhou...@gmail.com<mailto:matthieuvanhou...@gmail.com>> a écrit :
Dear Freesurfer's experts,
In order to have a robust PET signal projection, is it possible compute the
projected PET signal as a weighted average of the PET signal intersecting with
the surfaces ranging from 35 to 65% of the cortical tickness with a step t=5% ?
More weight would be given to the surfaces located near the mid distance
between the pial and white surfaces as they have a higher probability to be
well located within the cortex (using a normal distribution for example).
Thank you for helping.
Best,
Matthieu
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