Dear Bruce, Thank again for your kind help. I’m running version 5.1.0.
Below is the output of the command.
I also ran it with parea=0 but almost no change in the result (see the
attachment-1)
I also plot the sluci map for comparison (see the attachment-2) but still
not satisfactory.[IMAGE][IMAGE]
Best
~/Data/P00001613/FreeSurferClean/surf\> mris_register -1 -curv -dist .25
lh.sphere ../../../P00001639/FreeSurferClean/surf/lh.sphere
lh.sphere_dis25.reg
treating target as a single subject's surface...
using smoothwm curvature for final alignment
l_dist = 0.250
$Id: mris_register.c,v 1.59 2011/03/02 00:04:33 nicks Exp $
$Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $
reading surface from lh.sphere...
reading spherical surface
../../../P00001639/FreeSurferClean/surf/lh.sphere...
curvature mean = -0.000, std = 1.000
computing parameterization for surface
../../../P00001639/FreeSurferClean/surf/lh.inflated.H...
curvature mean = 0.000, std = 0.566
computing parameterization for surface
../../../P00001639/FreeSurferClean/surf/lh.sulc...
curvature mean = -0.030, std = 0.282
computing parameterization for surface
../../../P00001639/FreeSurferClean/surf/lh.smoothwm...
MRISregister() -------
max_passes = 4
min_degrees = 0.500000
max_degrees = 64.000000
nangles = 8
tol=5.0e-01, sigma=0.0, host=unkno, nav=1024, nbrs=1, l_extern=10000.000,
l_parea=0.100, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
complete_dist_mat 0
rms 0
smooth_averages 0
remove_neg 0
ico_order 0
which_surface 0
target_radius 0.000000
nfields 0
scale 0.000000
desired_rms_height -1.000000
momentum 0.950000
nbhd_size -10
max_nbrs 10
niterations 25
nsurfaces 0
SURFACES 3
flags 16 (10)
use curv 16
no sulc 0
no rigid align 0
mris->nsize 1
mris->hemisphere 0
randomSeed 0
--------------------
tol=5.0e-01, sigma=0.0, host=unkno, nav=1024, nbrs=1, l_extern=10000.000,
l_parea=0.100, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
1 Reading lh.sulc
curvature mean = 0.000, std = 0.583
curvature mean = 0.044, std = 0.847
curvature mean = 0.022, std = 0.852
Starting MRISrigidBodyAlignGlobal()
d=32.00 min @ (8.00, 0.00, 0.00) sse = 90765.7, tmin=0.9987
d=16.00 min @ (-4.00, -4.00, 0.00) sse = 87371.6, tmin=1.5086
d=8.00 min @ (-2.00, 0.00, 0.00) sse = 86754.0, tmin=2.0493
d=4.00 min @ (1.00, 1.00, 0.00) sse = 86449.9, tmin=2.5976
d=2.00 min @ (0.00, -0.50, 0.50) sse = 86436.5, tmin=3.1563
d=1.00 min @ (0.00, 0.25, -0.25) sse = 86423.4, tmin=3.6949
MRISrigidBodyAlignGlobal() done 4.24 min
curvature mean = 0.036, std = 0.923
curvature mean = 0.010, std = 0.931
curvature mean = 0.036, std = 0.951
curvature mean = 0.004, std = 0.967
curvature mean = 0.036, std = 0.962
curvature mean = 0.001, std = 0.984
2 Reading smoothwm
curvature mean = -0.027, std = 0.269
tol=1.0e+00, sigma=0.5, host=unkno, nav=1024, nbrs=1, l_extern=10000.000,
l_parea=0.100, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
curvature mean = 0.090, std = 0.337
curvature mean = 0.059, std = 0.386
curvature mean = 0.091, std = 0.507
curvature mean = 0.020, std = 0.580
curvature mean = 0.091, std = 0.618
curvature mean = 0.011, std = 0.723
curvature mean = 0.093, std = 0.681
curvature mean = 0.004, std = 0.828
MRISregister() return, current seed 0
expanding nbhd size to 1
writing registered surface to lh.sphere_dis25.reg...
--
Ray Razlighi, Ph.D.
Assistant Professor
Quantitative Neuroimaging Laboratory
Division of Cognitive Neuroscience
Department of Neurology
Columbia University
Alt: razli...@gmail.com
Office Phone: 212-342-1352
Office Fax: 212-342-1838
Website: http://www.columbia.edu/cu/qnl/
On Nov 4, 2015, at 7:30 PM, Bruce Fischl <fis...@nmr.mgh.harvard.edu> wrote:
Hi Ray
what version of FS are you using? Can you send me the output of
the command? The distance term will prevent the curvatures from
deforming too much. You can set it much smaller and see what
happens if you want. There may also be an area constraint.
Trying using -parea 0 also (or something small)
cheers
Bruce
On Wed, 4 Nov 2015, Razlighi, Qolamreza R. wrote:
Hi Bruce,
Thanks for reply. I thought after registering, the
source surface's curvature map should be very
similar to the target one. I don't see that here.
The registered surface has pretty much the same
curvature map only slightly shifted.
Am I missing something here?
Best
On Nov 4, 2015, at 5:56 PM, Bruce Fischl
<fis...@nmr.mgh.harvard.edu>
wrote:
Hi Ray
that sounds right. The way I visualize
these is using nmovie (which I think we
include in our distribution) and
flipping back and forth between the
different images showing the different
surfaces/curv maps.
Which inaccuracy are you referring to?
cheers
Bruce
On Wed, 4 Nov 2015, Razlighi, Qolamreza
R. wrote:
Dear Bruce,
I did run it again with
option (-dist 0.25); however
the result did not
change much (See the
attachment). These results
do not seem right to me and
I think I’m running the
command correctly (see the
first email). However,
I’m not sure I’m visualizing
the curvature maps
correctly. I assume the
lh.sphere.reg has the same
vertices and facets as
lh.sphere but slightly
displaced in space to match
the curvature and sulci map
of the source
surface to target surface.
Therefore, I visualize the
lh.sphere.reg by
pulling the same lh.curv
file from the source image.
If this is wrong,
please let me know how can I
correctly visualize the
lh.sphere.reg,
otherwise I have no idea why
this surface based
registration produce such
inaccurate results. Any
comments or suggestion is
greatly appreciated.
Best
[IMAGE]
--
Ray Razlighi, Ph.D.
Assistant Professor
Quantitative Neuroimaging
Laboratory
Division of Cognitive
Neuroscience
Department of Neurology
Columbia University
Alt: razli...@gmail.com
Office Phone: 212-342-1352
Office Fax: 212-342-1838
Website:
http://www.columbia.edu/cu/qnl/
On Nov 3, 2015, at 3:47 PM,
Bruce Fischl
<fis...@nmr.mgh.harvard.edu>
wrote:
Hi Ray
the -1 means that the
target is a single surface
and not an
atlas, but the
registration is still
nonlinear. The variances
will all be 1 so you may
have to play with the
weights in the
energy functional. We
don't do this very much and
it probably
defaults to quite rigid.
Try reducing the weight on
the metric
preservation term (e.g.
-dist .25) if you want it to
be more
nonlinear
cheers
Bruce
On Tue, 3 Nov 2015,
Razlighi, Qolamreza R.
wrote:
Hi Guys,
I read in the
sidenote here
(https://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceRegAndTemplates
)
that
inter-subject
surface base registration
using
mris_register and
-1 flag
performs a sort of
rigid registration. So I
tried it
between two of my
subjects with the
command below
mris_register -1
-curv
P00001639/FreeSurferClean/surf/lh.sphere
P00001639/FreeSurferClean/surf/lh.sphere
lh.sphere3.reg
and got the
results (see the
attachment). It is
clear that the
registration
output is just a
shifted version of the
source.
Having this
confirmed I want
to know if there
is any way to force the
mris_register to
perform a complete
non-linear surface
based registration for
inter-subjects
registration the
same way it does
for template.
I have to mention
that I visualize the
lh.sphere3.reg
using freeview and
loaded the sane
lh.curv on that surface. I
hope I’m
not doing anything
stupid.
[IMAGE]
Best
--
Ray Razlighi,
Ph.D.
Assistant
Professor
Quantitative
Neuroimaging Laboratory
Division of
Cognitive Neuroscience
Department of
Neurology
Columbia
University
Alt:
razli...@gmail.com
Office Phone:
212-342-1352
Office Fax:
212-342-1838
Website:
http://www.columbia.edu/cu/qnl/
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