Hi all,
I want to extract to extract thickness, area and lgi values vertex wise
in ascii files for group of subjects. Could anyone suggest me on how to do it.
Thank you for your help.
-Sabin___
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard
Hi Sabin
mris_convert can convert binary "curvature" format files to ascii ones if
the output file has the extension asc. Something like:
mris_convert -c lh.thickness lh.orig lh.thickness.asc
this will give you a 5 column ascii file in the format
cheers
Bruce
On Thu, 17 Apr 2014,
sabin
yes, you can use mri_surf2surf first to map them to fsaverage, then
convert them to ascii
On Thu, 17 Apr 2014, sabin khadka wrote:
> Hi Bruce,
> Thanks for the reply. I was wondering if I have to somehow resample or map
> to fsaverage so as to have same # of vertices across all subjects. I tried
Hi Bruce,
Thanks for the reply. I was wondering if I have to somehow resample or map to
fsaverage so as to have same # of vertices across all subjects. I tried using
mris_convert as you suggested above but I can see that different subjects have
different #of vertices.
Thanks for help.
-Sabin
Thanks Bruce! I will try it again then!
Katica
From: freesurfer-boun...@nmr.mgh.harvard.edu
[freesurfer-boun...@nmr.mgh.harvard.edu] on behalf of Bruce Fischl
[fis...@nmr.mgh.harvard.edu]
Sent: Wednesday, April 16, 2014 10:10 PM
To: Freesurfer support list
Subje
Hello, I have a question about how to get freesurfer to work correctly with
images that have problematic contrast.
We have a bunch of images that were taken with a new 32-channel head coil. For
some of these images, the contrast value for the scalp cutaneous fat is
dramatically higher than the
Anyone have any input?
On Apr 16, 2014, at 11:27 AM, Jonathan Holt wrote:
> Doug,
>
> Thanks for the quick reply.
>
> At this point all I want to do is calculate average thickness, per group,
> then visualize the average whole brain thickness for each group. I’m thinking
> I’m probably going
We are working on a study that includes data from multiple scanners and initial
indication suggest that there may be small differences in cortical thickness
measures that are scanner related (human and other phantom data were acquired
at both sites).
Is it possible to include a correction facto
Hi all,
I ran mri_surf2surf and then mris_convert to get vertexwise thickness and
surface
area values in ascii files. I found that some vertices had negative values
of surface area for few subjects. Should not surface area values be
positive only?
-Sabin
On Thursday, April 17, 2014 10:30 AM, s
I'm a little lost here. Why would you run mris_preproc with the average
subject as input? That is not one of the options I listed below. It
sounds like you would run mris_preproc with fsaverage as the target and
your list of subjects for a group as input. Then take the mean of the
output stack
I would probably just include scanner as a nuisance variable. Can you do
that?
On 04/17/2014 12:07 PM, David Tate wrote:
> We are working on a study that includes data from multiple scanners
> and initial indication suggest that there may be small differences in
> cortical thickness measures t
Doug
thank you for your patience. for you what seems natural can be a bit confusing
for me. I'll do what you suggests, but I have to ask where does
make_average_subject come into play. you recommended it as an option, but now
it doesn't seem to be
a part of the process
Jon
> On Apr 17, 2014
If you want to display the group mean on the average anatomy of your
group, then you use make_average_subject. This is different that just
creating an average map of cortical thickness (as is done with
mris_preproc). make_average_subject actually creates surfaces, the whole
freesurfer subject
Dear freesurfer experts,
As far as I understand, dt_recon uses linear least squares method as
default to estimate the diffusion tensor. Is it possible to use weighted
linear least squares in dt_recon?
Thank you.
Estephan Moana-Filho, DDS, MS, PhD
Clinical Fellow, Oral & Maxillofacial Pain Pr
In principle if you knew the weights you could weight each direction
(but not across weights). But it will not compute such weights for you
doug
On 4/17/14 7:35 PM, Estephan Moana wrote:
Dear freesurfer experts,
As far as I understand, dt_recon uses linear least squares method as
default
Hi FS experts,
I have a ROI mask in tlrc coordinates in *.tlrc file format, which represents
functional activation. Also I have a significant area in sig.mgh which
represents cortical thickness difference between two groups, and I created a
mask based on surface for it. Now I want to compare the
Hello Freesurfer experts,
I analysed my DTI data using dt_recon and the resulting fa.nii file. I did ROI
analyses using the fa values for each subject.
The data were acquired by Siemens 3T Trio-Tim.
When I reported the results, I was asked whether the directions were corrected
for slice angulati
17 matches
Mail list logo