Hi Bruce,I got this to work, but we are still having the same problem wth over-inclusion of pial matter in the white matter segmentations even when using skullstrip from other packages (AFNI , FSL, ANTs).I am mainly interested in the subcortical volumes, and I want to do a longitudinal analysis of the subcortical volumes. Does the longitudinal freesurfer pipeline depend on good quality segmentation across whole brain? or can I use it to obtain longitudinal subcortical volumes and ignore the fact that the white matter segmentation is less than perfect for many subjects? Is it a problem that the whole-brain volume measures will be off due to the over-inclusion of skull in WM?I would appreciate any advice or insights you may have!Thanks,MichelleOn Wed, Aug 9, 2017 at 6:39 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:are you sure you created the brainmask with -rl orig.mgz? It should have the same dimensions afterwards.
On Wed, 9 Aug 2017, Michelle VanTieghem wrote:
-bash-4.1$ mri_info orig.mgz
Volume information for orig.mgz
type: MGH
dimensions: 256 x 256 x 256
voxel sizes: 1.0000, 1.0000, 1.0000
type: UCHAR (0)
fov: 256.000
dof: 0
xstart: -128.0, xend: 128.0
ystart: -128.0, yend: 128.0
zstart: -128.0, zend: 128.0
TR: 0.00 msec, TE: 0.00 msec, TI: 0.00 msec, flip angle: 0.00
degrees
nframes: 1
PhEncDir: UNKNOWN
ras xform present
xform info: x_r = -1.0000, y_r = 0.0000, z_r = 0.0000, c_r =
-5.2291
: x_a = 0.0000, y_a = 0.0000, z_a = 1.0000, c_a =
3.0505
: x_s = 0.0000, y_s = -1.0000, z_s = 0.0000, c_s =
-0.9364
talairach xfm :/vega/psych/users/mrv2115/fsdata/processed/SB020_fu1/mri/tr ansforms/talaira
ch.xfm
Orientation : LIA
Primary Slice Direction: coronal
voxel to ras transform:
-1.0000 0.0000 0.0000 122.7709
0.0000 0.0000 1.0000 -124.9495
0.0000 -1.0000 0.0000 127.0636
0.0000 0.0000 0.0000 1.0000
voxel-to-ras determinant -1
ras to voxel transform:
-1.0000 0.0000 0.0000 122.7709
-0.0000 -0.0000 -1.0000 127.0636
-0.0000 1.0000 -0.0000 124.9495
0.0000 0.0000 0.0000 1.0000
------------------------------------------------------------ ---------------
-------------
-bash-4.1$ mri_info brainmask.mgz
Volume information for brainmask.mgz
type: MGH
dimensions: 221 x 274 x 261
voxel sizes: 1.0000, 1.0000, 1.0000
type: SHORT (4)
fov: 274.000
dof: 0
xstart: -110.5, xend: 110.5
ystart: -137.0, yend: 137.0
zstart: -130.5, zend: 130.5
TR: 0.00 msec, TE: 0.00 msec, TI: 0.00 msec, flip angle: 0.00
degrees
nframes: 1
PhEncDir: UNKNOWN
ras xform present
xform info: x_r = -1.0000, y_r = 0.0000, z_r = 0.0000, c_r =
-5.2291
: x_a = 0.0000, y_a = -1.0000, z_a = 0.0000, c_a =
3.0505
: x_s = 0.0000, y_s = 0.0000, z_s = 1.0000, c_s =
-0.9364
talairach xfm :
Orientation : LPS
Primary Slice Direction: axial
voxel to ras transform:
-1.0000 0.0000 0.0000 105.2709
0.0000 -1.0000 0.0000 140.0505
0.0000 0.0000 1.0000 -131.4364
0.0000 0.0000 0.0000 1.0000
voxel-to-ras determinant 1
ras to voxel transform:
-1.0000 0.0000 0.0000 105.2709
0.0000 -1.0000 0.0000 140.0505
-0.0000 -0.0000 1.0000 131.4364
0.0000 0.0000 0.0000 1.0000
------------------------------------------------------------ ---------------
------------------------------
Iterating 2 times
---------------------------------
3d normalization pass 1 of 2
white matter peak found at 111
white matter peak found at 110
gm peak at 84 (84), valley at 0 (-1)
csf peak at 42, setting threshold to 70
building Voronoi diagram...
performing soap bubble smoothing, sigma = 8...
---------------------------------
3d normalization pass 2 of 2
white matter peak found at 111
white matter peak found at 110
gm peak at 83 (83), valley at 0 (-1)
csf peak at 41, setting threshold to 69
building Voronoi diagram...
performing soap bubble smoothing, sigma = 8...
Done iterating ---------------------------------
writing output to brain.mgz
3D bias adjustment took 4 minutes and 23 seconds.
#--------------------------------------------
#@# Mask BFS Wed Aug 9 02:03:44 EDT 2017
/vega/psych/users/mrv2115/fsdata/processed/SB020_fu1/mri
mri_mask -T 5 brain.mgz brainmask.mgz brain.finalsurfs.mgz
threshold mask volume at 5
ERROR: dimension mismatch between source and mask
Linux reno.cc.columbia.edu 2.6.32-696.el6.x86_64 #1 SMP Tue Feb 21 00:53:17
EST 2017 x86_64 x86_64 x86_64 GNU/Linux
recon-all -s SB020_fu1 exited with ERRORS at Wed Aug 9 02:03:46 EDT 2017
On Wed, Aug 9, 2017 at 4:11 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu>
wrote:
can you send us the output of mri_info on orig.mgz and
brainmask.mgz created with the -rl flag? And also send us the
full screen output of the command that fails?
thanks
Bruce
On Wed, 9 Aug 2017, Michelle VanTieghem wrote:
Hi,
I originally used
mri_convert orig.mgz afni_stripped_volume.brik
brainmask.mgz
and I re-did it using the -rl flag as you
recommended.
it did not influence anything, same problem.
I'd appreciate any trouble shooting tips.
Thanks,
M
On Mon, Aug 7, 2017 at 5:45 PM, Bruce Fischl
<fischl@nmr.mgh.harvard.edu>
wrote:
what was your mri_convert command line? It
should be something
like
mri_convert -rl orig.mgz
afni_stripped_volume.brik brainmask.mgz
cheers
Bruce
On Mon, 7 Aug 2017, Michelle VanTieghem wrote:
Hi Bruce,
Here is what I did. For each subject:
a) used the original (non-skull
stripped) brain for
the 001.mgz file as input -
located in the Subnum/mri directory
b) used mri_convert to get the afni
skull-stripped
brains and renamed them
"brainmask.mgz" , located in the
Subnum/mri
directory.
c) Then I ran the following command:
recon-all -all -3T -mprage -s
processed/Subnum
I get the following error:
--------------------------------------------------
#@# Mask BFS Sat Aug 5 01:31:09 EDT
2017
/vega/psych/users/mrv2115/fsdata/processed/SB002/mri
mri_mask -T 5 brain.mgz brainmask.mgz
brain.finalsurfs.mgz
threshold mask volume at 5
ERROR: dimension mismatch between source
and mask
-------------------------------------------------
Can you please advise?
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Michelle VanTieghem
PhD student in Psychology
Developmental Affective Neuroscience Lab
Columbia University
mrv2115@columbia.edu
--
Michelle VanTieghem
PhD student in Psychology
Developmental Affective Neuroscience Lab
Columbia University
mrv2115@columbia.edu
--Michelle VanTieghemPhD student in PsychologyDevelopmental Affective Neuroscience LabColumbia University