Hi Jürgen,
We are using a 7T
from Siemens and we acquire two volumes with an MPRAGE and 3D GE sequence. Using
SPM both volumes are co-registered and afterwards the MPRAGE is divided by the
3D GE. Attached is a sample *.jpg showing the results.
In our case the
temporal lobes are still not very homogeneous due to some problems with the coil
or gradient system (currently a new gradient is being installed, so it probably
will help). Also I’m further improving the volumes by running mri_nu_correct.mni
on the T1.mgz created by the normalization stage (like mri_nu_correct.mni –stop
0.001 –distance 25 –i T1.mgz –o nu.mgz) and running mri_normalize
again afterwards. The volume normally looks very homogeneous afterwards, even
the temporal lobes.
But I’m
facing problems in the following stages, mainly everything based on the aseg files
as I need to skip the process. I can’t recall exactly during which stage,
but recon-all exists with the error that the aseg.mgz needs to be conformed, so
it needs to be skipped. But by skipping these stages I currently have issues
during mri_fill as the cerebellum is not erased as it should be.
Also the skull
stripping isn’t very good in most cases. The only solution I had was
using a brainmask created by Slicer or to run recon-all normally (conforming
the data) and resampling the brainmask to the original resolution (using
mri_vol2vol). Then masking the T1.mgz to get a fairly good looking brainmask.
Hope this helps,
Regards,
Falk
From: Jürgen Hänggi
[mailto:j.haenggi@psychologie.uzh.ch]
Sent: Monday, May 18, 2009 3:30 PM
To: Falk Lüsebrink
Subject: Re: [Freesurfer] Measuring cortical thickness with high
resolution data
Hi Falk
We are also struggling with 7T images and Freesurfer. In your email (see below)
you wrote that you have find a way to get ride of the inhomogeneities inherent
in the 7T images. Which other sequence did you use for that? Do you also use a
7T scanner from Philips? Do you use an adiabatic pulse sequence?
Thanks in advance
Best regards
Jürgen
On [DATE], "Falk Lüsebrink" <[ADDRESS]> wrote:
Hi
Freesurfers,
I’m trying to evaluate the usefulness of high resolution scans acquired
at 7T with an isometric voxel size of .6mm for the measurement of cortical
thickness. The inhomogeneities are taken care of by dividing the scans with
another scan of another sequence, so they are not an issue anymore.
My problem is that Freesurfer usually conforms the voxel size to 1mm which is
not desirable. I tried using the –cm and –noaseg flags for the
recon-all process to avoid the conformation and to skip the subcortical
segmentation, but another problem arises while using these flags.
The error I receive is occurring after the WM Segmentation and states as
follows:
#--------------------------------------------
#...@# WM Segmentation Wed Mar 18 10:14:42 CET 2009
cp wm.mgz wm.seg.mgz
mri_segment -keep brain.mgz wm.seg.mgz
preserving editing changes in output volume...
doing initial intensity segmentation...
using local statistics to label ambiguous voxels...
computing class statistics for intensity windows...
WM (106.0): 106.9 +- 5.8 [80.0 --> 125.0]
GM (69.0) : 66.3 +- 11.6 [30.0 --> 96.0]
setting bottom of white matter range to 77.9
setting top of gray matter range to 89.4
doing initial intensity segmentation...
using local statistics to label ambiguous voxels...
using local geometry to label remaining ambiguous voxels...
reclassifying voxels using Gaussian border classifier...
removing voxels with positive offset direction...
smoothing T1 volume with sigma = 0.250
removing 1-dimensional structures...
thickening thin strands....
20 segments, 4813 filled
10270 bright non-wm voxels segmented.
5589 diagonally connected voxels added...
white matter segmentation took 2.4 minutes
writing output to wm.seg.mgz...
ERROR: mri_segment-MRIcheckVolDims: volume1 height=256 != volume2 height=320.
The dimensions of the data I’m trying to process is 320 x 320 x 224 and
is changed to 320 x 320 x 320 while using the –cm flag. It seems the
mri_segment process can’t handle any dimensions above 256 or I’m
missing another flag.
Does someone has any ideas about that issue?
Regards,
Falk
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Juergen Haenggi
Ph.D. (Dr. des.)
Division Neuropsychology
Institute of Psychology
University of Zurich
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