On Tue, 13 Oct 2009, Angel Wong wrote:
Hi Bruce
I have downloaded the latest version (v4.5.0) and tried again. But
unfortunately, I cannot reproduce the results same as yours. The new
generated results are similar to the results generated by the older version.
The command I used is
recon-all -i <directory that contains COR files> -s <subjectid> -sd
<subjects_dir> -all
and I viewed the images using
tkmedit <subjectid> brainmask.mgz lh.white -aux-surface rh.white
I am wondering why there is a big difference between your results and mine.
Is there any pre-setting needed before running the recon-all or additional
arguments needed during the processing?
Cheers
Angel
2009/10/11 Angel Wong <angel.delver@gmail.com>
Hi Nick
Thanks for your suggestion. I will look at it in detail later.
Angel
2009/10/10 Nick Schmansky <nicks@nmr.mgh.harvard.edu>
Angel,
I noticed you have problems with some remaining dura in your images. you
might want to try a new utility that is being tested for inclusion in a
future release. Its from a group in Singapore, and does a good job
removing dura. Its called:
mri_gcut
and can be downloaded for the linux and mac platforms from here:
ftp://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/misc/
copy it to your $FREESURFER_HOME/bin
usage (with reference to paper) is found in:
mri_gcut --help
and intended usage is:
cd subjid/mri
mri_gcut -110 -mult brainmask.mgz T1.mgz brainmask.mgz
then run:
recon-all -s subjid -autorecon2 -autorecon3
but of course inspect the brainmask.mgz to see if actually helped.
(bruce, can you point me at her image? i can run it locally)
Nick
On Sat, 2009-10-10 at 21:46 +0800, Angel Wong wrote:
My version is 4.3.0. I will download the latest version and try again.
Thank you.
2009/10/10 Bruce Fischl <fischl@nmr.mgh.harvard.edu>
I didn't do anything but run recon-all with the latest
version. Remind me what version you were running?
On Sat, 10 Oct 2009, Angel Wong wrote:
Hi Bruce
Thank you very much. The result looks much better than
mine. How did you do
that? Please let me know so that I can modify the
other datasets if I face
the same situation again.
Cheers
Angel
2009/10/10 Bruce Fischl <fischl@nmr.mgh.harvard.edu>
Hi Angel,
I'm just about done running the dataset and
the results actually look ok
(see attached tif). I didn't intervene at all,
although you would want to to
get rid of some non-brain tissue that the pial
surface is grabbing, but
that's pretty easy. Did you minimize your TE?
I don't know what your
gradient set is, but usually you can get your
TE down a bit more than that.
You also might be better off sacrificing a bit
of resolution and lengthening
your TR
cheers,
Bruce
On Thu, 8 Oct 2009, Angel Wong wrote:
Thanks a lot with your help. This is because
we want to perform quite a
number of functional runs on the same
subject at the same session. So we
tried to shorten the T1 scan time to
minimize the motion artifacts come
from
the subject.
Attached please find the orig.mgz for
your information.
2009/10/8 Bruce Fischl
<fischl@nmr.mgh.harvard.edu>
I see. Your TR is quite short and
your TE relatively long, so this is
probably pretty poor CNR
between gray and white. If you
send me the
orig.mgz
I'll take a look and see if
it's fixable
On Thu, 8 Oct 2009, Angel Wong
wrote:
Hi Bruce
Attached please find
the parameters for
acquiring the T1
image.
Thank you for your
help.
Angel
2009/10/8 Bruce Fischl
<
fischl@nmr.mgh.harvard.edu>
eek, that looks
pretty bad. Can you
tell us what the
acquisition
parameters
are?
On Thu, 8 Oct
2009, Angel
Wong wrote:
Dear all
Actually
I would like to perform automated reconstruction for my T1
image
and
then
obtain
anatomical labels after cortical parcellation. I have
done
fully
automated reconstruction using recon-all. But for my case, the
white
and
grey
matter
segmentation appears to be weird. The green line seems
laying
on the
pial
surface
rather than on the white surface, and the
red
line
seems
including some non-brain structures (including small
portion
of
CSF
and
skull).
Thus, the resultant cortical thickness appears to be
very
thin
after
the
segmentation. I just doubt if anything was going wrong
during
the
procedure. Or need any preprocessing to enhance the segmentation
quality
before
performing the reconstruction? If you have had similar
situation
as
mine,
please
let me
know
how to
tackle
the
problem.
Attached
please find the images for better illustration.
fs_image_brain.tiff - use brain.mgz as aux volume
fs_image_norm.tiff - use norm.mgz as aux volume
fs_image_brainmask.tiff - use brainmask.mgz as aux volume and load
segmentation file aseg.mgz
Thanks
Angel
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