Dear Freesurfer list,
Using the optseq2 program, is it possible to calculate the efficiency of a
custom par file? I have an fMRI task that will be split into three blocks.
I want to calculate the overall efficiency of my overall design
byconcatenating the best par file from optimizing each
Hi Freesurfer experts,
I am trying to use the clusters to run BedpostX on a Connectome
dataset.
Although the job is running now, it is running slowly. It has only got
though 18 slices over the last 10 hours:
pbsubmit -n 8 -m bl744 -c "bedpostx
Is is a warning or an error?
Passing the --disable-Werror flag to the configure script will prevent the
build from erroring out if it comes across a warning from the compiler. I
havent testing on Ubuntu 15 but I will give it a shot early early next
week.
-Zeke
> I'm preparing to migrate over to
Hi Bruce,Thank you for response. This is the output message:$ mri_convert -rt nearest --like template.nii.gz label.nii.gz label_nn.nii.gzmri_convert -rt nearest --like template.nii.gz label.nii.gz label_nn.nii.gz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $reading from
I'd like to open with FSLview the sig.nii.gz which is produced by
selxavg3-sess.
If I use mri_surf2vol, which is the template to added in --template?
It should be in Tailairach space? Where can I find the template that I
should added?
Thanks,
Stefano
Dear List,
I am facing a similar problem as described by Knut Bjuland:
http://www.mail-archive.com/freesurfer%40nmr.mgh.harvard.edu/msg39745.html
I could not find a public reply in the mailing list archives.
Therefore I would like to know whether it would be safe to either
downgrade
Dear all,
I wish to know whether mri_convert provide a nifty way to reslice and crop a
NIFTI image with labels (positive integers) with “—like” and “-rt” options. It
seems like “—like” option overrides “-rt” option, thus the result from such a
command:
> mri_convert -rt nearest —like
It is -openmp 8
Delete the less than and greater than characters around the 8
> On 16 Oct 2015, at 3:25 PM, Linda BOUMGHAR wrote:
>
> I would like to use freesurfer with OpenMP, with 4 processors. I wrote this :
> recon-all -all -i
>
Dear freesurfer developers,
Following the previous e-mail, it seems like a variable handling bug.
From the mri_convert.c, lines from 2588 to 2606 appear to be the part that
handles “out_like” option. the variable “resample_type_val” in line 2605 should
contain the user-specified value, but it
Dear all,
in reply to myself as a documentation for others: I tried a recent
development version of mri_convert. Instead of crashing, this version
instructed me to get a new license file for systems running GNU glibc
version greater 2.15. The new license file (.license, not license.txt)
Dear experts,
I am sending the example subject named chiasma_question.tar.gz to your FTP
server.
The issue with encircling chiasma is located in slices ~134-140.
According to Aparc.a2009s+aseg the tissue is marked as optical chiasm, but also
part of it is labeled as left cerebral white
Hi Linda
did you actually include the angle brackets? If so, try without them. And
don't you want 4 there instead of 8 (if you have 4 processors)?
On
Fri, 16 Oct 2015, Linda BOUMGHAR wrote:
> I would like to use freesurfer with OpenMP, with 4 processors. I wrote this :
> recon-all -all -i
>
Hi Seung-Goo
I would have that that your command line would work as is. Can you send
us the full screen output?
cheers
Bruce
On Fri, 16 Oct 2015, Seung-Goo KIM wrote:
Dear all,
I wish to know whether mri_convert provide a nifty way to reslice and crop a
NIFTI
image with labels (positive
Hi Kaspar,
It doesn't matter where you place the flags in your command line, as long as
all of them are there. Also, -s and -subjid are equivalent, so the first two
commands would be the same (although the path to your input data is different
after the -i flag, and your subject name is
Dear experts,
I want to run recon-all on a stripped brains ( T1 images after applying bet tool).
Do I need to add any flags to the command recon -all -all subjid
Bests,
John
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Hi Pablo
Yes, too many locations at which the estimation algorithm didn't converge is
problematic. That might mean that having two random effects is not appropriate
for your data. You should try to run the command with just a single random
effect for the intercept term:
lhstats =
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