External Email - Use Caution
Hi all,
I wanted to follow up on Courtney Haswell’s previous email – we’re still running into the error where the hippocampal files aren’t being created when we run our scans through the recon_all using the -hippocampal-subfields flag. I’ve included the hippocampal log file below. Do you have any insight on why this might be happening?
Thanks, Emily Clarke-Rubright
The whole log message:
#--------------------------------------------
#@# Hippocampal Subfields processing (T1 only) left Mon Aug 10 18:54:21 EDT
2020
------------------------------------------
Setting up environment variables
---
LD_LIBRARY_PATH is
.:/usr/local/packages/freesurfer_v6.0.0/MCRv80/runtime/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/bin/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/os/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/native_threads:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/server:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/client:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64:/usr/lib64/qt5/plugins/platforms:/usr/local/packages/ants-2.3.4/lib:/usr/lib64/openmpi/lib:
Warning: application is running on a locale different from the original
platform locale.
Warning: No display specified. You will not be able to display graphics on
the screen.
Registering imageDump.mgz to hippocampal mask from ASEG
This file does not contain MRI parameters
$Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $
--mov: Using imageDump.mgz as movable/source volume.
--dst: Using /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz
as target volume.
--lta: Output transform as trash.lta .
--mapmovhdr: Will save header adjusted movable as
imageDump_coregistered.mgz !
--sat: Using saturation 50 in M-estimator!
reading source 'imageDump.mgz'...
reading target '/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz'.
..
Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )
Type Source : 0 Type Target : 3 ensure both FLOAT (3)
Reordering axes in mov to better fit dst... ( -1 3 -2 )
MRIreorder() -----------
xdim=-1 ydim=3 zdim=-2
src 131 241 99, 0.250000 0.250000 0.250000
dst 131 99 241, 0.250000 0.250000 0.250000
Determinant after swap : 0.015625
Mov: (0.25, 0.25, 0.25)mm and dim (131, 99, 241)
Dst: (1, 1, 1)mm and dim (38, 40, 59)
Asserting both images: 1mm isotropic
- reslicing Mov ...
-- changing data type from 0 to 3 (noscale = 0)...
-- Original : (0.25, 0.25, 0.25)mm and (131, 99, 241) voxels.
-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
- reslicing Dst ...
-- Original : (1, 1, 1)mm and (38, 40, 59) voxels.
-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
Registration::computeMultiresRegistration
- computing centroids
- computing initial transform
-- using translation info
- Get Gaussian Pyramid Limits ( min size: 16 max size: -1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- initial transform:
Ti = [ ...
1.0000000000000 0 0 1.1459029727155
0 1.0000000000000 0 -0.0876360601093
0 0 1.0000000000000 -2.9034875996918
0 0 0 1.0000000000000 ]
- initial iscale: Ii =1
Resolution: 1 S( 19 20 30 ) T( 19 20 30 )
Iteration(f): 1
-- diff. to prev. transform: 7.11234
Iteration(f): 2
-- diff. to prev. transform: 5.92976
Iteration(f): 3
-- diff. to prev. transform: 7.00993
Iteration(f): 4
-- diff. to prev. transform: 4.91305
Iteration(f): 5
-- diff. to prev. transform: 0.781018 max it: 5 reached!
Resolution: 0 S( 38 40 61 ) T( 38 40 61 )
Iteration(f): 1
-- diff. to prev. transform: 8.1296
Iteration(f): 2
-- diff. to prev. transform: 1.32542
Iteration(f): 3
-- diff. to prev. transform: 0.660013
Iteration(f): 4
-- diff. to prev. transform: 0.272219
Iteration(f): 5
-- diff. to prev. transform: 0.0943126 max it: 5 reached!
- final transform:
Tf = [ ...
0.9986737402682 -0.0371977207162 0.0355962086772 0.4749903609000
0.0194355513105 0.9126027300469 0.4083852549446 -14.0571487737101
-0.0476761978762 -0.4071517980857 0.9121153400046 9.9144950322154
0 0 0 1.0000000000000 ]
- final iscale: If = 1
**********************************************************
*
* WARNING: Registration did not converge in 5 steps!
* Problem might be ill posed.
* Please inspect output manually!
*
**********************************************************
Final Transform:
Adjusting final transform due to initial resampling (voxel or size changes)
...
M = [ ...
-0.2496684350671 0.0088990521693 0.0092994301791 34.3717771918614
-0.0048588878276 0.1020963137361 -0.2281506825117 16.0960341057205
0.0119190494690 0.2280288350011 0.1017879495214 -5.4978401025085
0 0 0 1.0000000000000 ]
Determinant : -0.015625
writing output transformation to trash.lta ...
converting VOX to RAS and saving RAS2RAS...
mapmovhdr: Changing vox2ras MOV header (to map to DST) ...
To check aligned result, run:
freeview -v /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz
imageDump_coregistered.mgz
Registration took 0 minutes and 1 seconds.
Thank you for using RobustRegister!
If you find it useful and use it for a publication, please cite:
Highly Accurate Inverse Consistent Registration: A Robust Approach
M. Reuter, H.D. Rosas, B. Fischl. NeuroImage 53(4):1181-1196, 2010.
http://dx.doi.org/10.1016/j.neuroimage.2010.07.020
http://reuter.mit.edu/papers/reuter-robreg10.pdf
$Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $
--mov: Using imageDump.mgz as movable/source volume.
--dst: Using /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz
as target volume.
--lta: Output transform as trash.lta .
--mapmovhdr: Will save header adjusted movable as
imageDump_coregistered.mgz !
--affine: Enableing affine transform!
--sat: Using saturation 50 in M-estimator!
reading source 'imageDump.mgz'...
reading target '/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz'.
..
Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )
Type Source : 0 Type Target : 3 ensure both FLOAT (3)
Reordering axes in mov to better fit dst... ( -1 3 -2 )
MRIreorder() -----------
xdim=-1 ydim=3 zdim=-2
src 131 241 99, 0.250000 0.250000 0.250000
dst 131 99 241, 0.250000 0.250000 0.250000
Determinant after swap : 0.015625
Mov: (0.25, 0.25, 0.25)mm and dim (131, 99, 241)
Dst: (1, 1, 1)mm and dim (38, 40, 59)
Asserting both images: 1mm isotropic
- reslicing Mov ...
-- changing data type from 0 to 3 (noscale = 0)...
-- Original : (0.25, 0.25, 0.25)mm and (131, 99, 241) voxels.
-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
- reslicing Dst ...
-- Original : (1, 1, 1)mm and (38, 40, 59) voxels.
-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
Registration::computeMultiresRegistration
- computing centroids
- computing initial transform
-- using translation info
- Get Gaussian Pyramid Limits ( min size: 16 max size: -1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- initial transform:
Ti = [ ...
1.0000000000000 0 0 1.1459028059189
0 1.0000000000000 0 -0.0876339827813
0 0 1.0000000000000 -2.9034861096682
0 0 0 1.0000000000000 ]
- initial iscale: Ii =1
Resolution: 1 S( 19 20 30 ) T( 19 20 30 )
Iteration(f): 1
-- diff. to prev. transform: 7.39891
Iteration(f): 2
-- diff. to prev. transform: 6.07128
Iteration(f): 3
-- diff. to prev. transform: 6.45354
Iteration(f): 4
-- diff. to prev. transform: 9.61165
Iteration(f): 5
-- diff. to prev. transform: 6.45157 max it: 5 reached!
Resolution: 0 S( 38 40 61 ) T( 38 40 61 )
Iteration(f): 1
-- diff. to prev. transform: 18.1397
Iteration(f): 2
-- diff. to prev. transform: 10.4781
Iteration(f): 3
-- diff. to prev. transform: 4.71708
Iteration(f): 4
-- diff. to prev. transform: 2.16703
Iteration(f): 5
-- diff. to prev. transform: 0.732237 max it: 5 reached!
- final transform:
Tf = [ ...
1.1003251237945 0.4596695415609 0.1319823678432 -15.3375075204562
-0.0809129505733 1.0958357713115 0.4294815397408 -16.7169936140805
-0.0871431123400 -0.3796938017010 0.9044729973197 10.3182069614882
0 0 0 1.0000000000000 ]
- final iscale: If = 1
**********************************************************
*
* WARNING: Registration did not converge in 5 steps!
* Problem might be ill posed.
* Please inspect output manually!
*
**********************************************************
Final Transform:
Adjusting final transform due to initial resampling (voxel or size changes)
...
M = [ ...
-0.2750812479116 0.0329955927294 -0.1149173912565 38.1277797083535
0.0202282358422 0.1073703848787 -0.2739589559572 15.8057165631404
0.0217857755217 0.2261182492690 0.0949234628220 -5.6011779490725
0 0 0 1.0000000000000 ]
Determinant : -0.0203612
Decompose into Rot * Shear * Scale :
Rot = [ ...
-0.9711353975406 0.1063152910440 -0.2135254048909
0.2376286779964 0.3535137619413 -0.9047434064484
0.0207038894236 0.9293681073764 0.3685732898005 ]
Shear = [ ...
1.0000000000000 -0.0073421724799 0.1576683162397
-0.0067818833526 1.0000000000000 -0.0678198022274
0.1779196232492 -0.0828533754661 1.0000000000000 ]
Scale = diag([ 0.2723989962754 0.2516119340902 0.3073865945084 ])
writing output transformation to trash.lta ...
converting VOX to RAS and saving RAS2RAS...
mapmovhdr: Changing vox2ras MOV header (to map to DST) ...
To check aligned result, run:
freeview -v /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz
imageDump_coregistered.mgz
Registration took 0 minutes and 1 seconds.
Thank you for using RobustRegister!
If you find it useful and use it for a publication, please cite:
Highly Accurate Inverse Consistent Registration: A Robust Approach
M. Reuter, H.D. Rosas, B. Fischl. NeuroImage 53(4):1181-1196, 2010.
http://dx.doi.org/10.1016/j.neuroimage.2010.07.020
http://reuter.mit.edu/papers/reuter-robreg10.pdf
Reading contexts of file
/usr/local/packages/freesurfer_v6.0.0/average/HippoSF/atlas/compressionLookupTable.txt
Constructing image-to-world transform from header information (asegMod.mgz)
Returning the following transform:
AffineTransform (0x2b5e6a48e220)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 422
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Offset: [132.04, -111.801, 144.75]
Center: [0, 0, 0]
Translation: [132.04, -111.801, 144.75]
Inverse:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Singular: 0
Constructing image-to-world transform from header information
(/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left/imageDump.mgz
)
Returning the following transform:
AffineTransform (0x2b5e6a48e220)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 579
Debug: Off
Object Name:
Observers:
none
Matrix:
0.275081 -0.0329956 0.114917
0.0217858 0.226118 0.0949235
-0.0202282 -0.10737 0.273959
Offset: [-38.0874, -33.402, 1.94475]
Center: [0, 0, 0]
Translation: [-38.0874, -33.402, 1.94475]
Inverse:
3.54297 -0.162038 -1.43002
-0.38743 3.81537 -1.15946
0.109759 1.48336 3.09018
Singular: 0
Transform before cropping:
AffineTransform (0x2b5e6a48e220)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 581
Debug: Off
Object Name:
Observers:
none
Matrix:
-0.275081 0.0329956 -0.114917
0.0202282 0.10737 -0.273959
0.0217858 0.226118 0.0949235
Offset: [170.128, 142.806, 78.3988]
Center: [0, 0, 0]
Translation: [170.128, 142.806, 78.3988]
Inverse:
-3.54297 1.43002 -0.162038
0.38743 1.15946 3.81537
-0.109759 -3.09018 1.48336
Singular: 0
WorldToImageTransform before cropping:
AffineTransform (0x2b5e6a47e8f0)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 583
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Offset: [132.04, 144.75, 111.801]
Center: [0, 0, 0]
Translation: [132.04, 144.75, 111.801]
Inverse:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Singular: 0
m_BoundingBoxSize: [131, 241,99]
minimalMappedCoordinate: [123.105, 115.958,78.3988]
maximalMappedCoordinate: [178.047, 171.204,144.802]
Cropping with min [118 110 72]
and max [184 177 151]
m_OriginalImageRegion before checking margins: ImageRegion (0x2b5e69a829b8)
Dimension: 3
Index: [118, 110, 72]
Size: [67, 68, 80]
m_CroppedImageRegion before checking margins: ImageRegion (0x2b5e69a82980)
Dimension: 3
Index: [0, 0, 0]
Size: [67, 68, 80]
m_OriginalImageRegion after checking margins: ImageRegion (0x2b5e69a829b8)
Dimension: 3
Index: [118, 110, 72]
Size: [67, 68, 80]
m_CroppedImageRegion after checking margins: ImageRegion (0x2b5e69a82980)
Dimension: 3
Index: [0, 0, 0]
Size: [67, 68, 80]
Transform after cropping:
AffineTransform (0x2b5e6a48e220)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 740
Debug: Off
Object Name:
Observers:
none
Matrix:
-0.275081 0.0329956 -0.114917
0.0202282 0.10737 -0.273959
0.0217858 0.226118 0.0949235
Offset: [52.1278, 32.8057, 6.39882]
Center: [0, 0, 0]
Translation: [52.1278, 32.8057, 6.39882]
Inverse:
-3.54297 1.43002 -0.162038
0.38743 1.15946 3.81537
-0.109759 -3.09018 1.48336
Singular: 0
WorldToImageTransform after cropping:
AffineTransform (0x2b5e6a47e8f0)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 741
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Offset: [14.0404, 34.7505, 39.8009]
Center: [0, 0, 0]
Translation: [14.0404, 34.7505, 39.8009]
Inverse:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Singular: 0
Transforming points
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Transforming points
Careful here: the applied transformation will turn positive tetrahedra into
negative ones.
-0.275081 0.0329956 -0.114917
0.0202282 0.10737 -0.273959
0.0217858 0.226118 0.0949235
determinant: -0.0203612
Starting to swap the point assignments of each tetrahedron...
Warning: This concatenation operation includes an empty array with an
incorrect number of rows.
Concatenation including empty arrays will require all arrays to have the
same number of rows in a future release.
[ > In segmentSubjectT1_autoEstimateAlveusML at 325]
Reading contexts of file
/usr/local/packages/freesurfer_v6.0.0/average/HippoSF/atlas/compressionLookupTable.txt
--------------
Making Lateral-nucleus map to reduced label 1
Making Paralaminar-nucleus map to reduced label 1
Making Basal-nucleus map to reduced label 1
Making Accessory-Basal-nucleus map to reduced label 1
Making Corticoamygdaloid-transitio map to reduced label 1
Making Central-nucleus map to reduced label 1
Making Cortical-nucleus map to reduced label 1
Making Medial-nucleus map to reduced label 1
Making Anterior-amygdaloid-area-AAA map to reduced label 1
--------------
Making alveus map to reduced label 2
Making Hippocampal_tail map to reduced label 2
Making HATA map to reduced label 2
Making fimbria map to reduced label 2
Making parasubiculum map to reduced label 2
Making hippocampal-fissure map to reduced label 2
--------------
Making Left-Cerebral-Cortex map to reduced label 3
--------------
Making Left-Cerebral-White-Matter map to reduced label 4
--------------
Making Left-Lateral-Ventricle map to reduced label 5
--------------
Making Left-choroid-plexus map to reduced label 6
--------------
Making Unknown map to reduced label 7
--------------
Making Left-VentralDC map to reduced label 8
--------------
Making Left-Putamen map to reduced label 9
--------------
Making Left-Pallidum map to reduced label 10
--------------
Making Left-Thalamus-Proper map to reduced label 11
--------------
Making Left-Accumbens-area map to reduced label 12
--------------
Making Left-Caudate map to reduced label 13
Error using segmentSubjectT1_autoEstimateAlveusML (line 348)
The vector of prior probabilities in the mesh nodes must always sum to one
over all classes
#--------------------------------------------
#@# Hippocampal Subfields processing (T1 only) right Mon Aug 10 18:54:37
EDT 2020
------------------------------------------
Setting up environment variables
---
LD_LIBRARY_PATH is
.:/usr/local/packages/freesurfer_v6.0.0/MCRv80/runtime/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/bin/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/os/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/native_threads:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/server:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/client:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64:/usr/lib64/qt5/plugins/platforms:/usr/local/packages/ants-2.3.4/lib:/usr/lib64/openmpi/lib:
Warning: application is running on a locale different from the original
platform locale.
Warning: No display specified. You will not be able to display graphics on
the screen.
Registering imageDump.mgz to hippocampal mask from ASEG
This file does not contain MRI parameters
$Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $
--mov: Using imageDump.mgz as movable/source volume.
--dst: Using /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz
as target volume.
--lta: Output transform as trash.lta .
--mapmovhdr: Will save header adjusted movable as
imageDump_coregistered.mgz !
--sat: Using saturation 50 in M-estimator!
reading source 'imageDump.mgz'...
reading target '/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz'.
..
Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )
Type Source : 4 Type Target : 3 ensure both FLOAT (3)
Reordering axes in mov to better fit dst... ( 1 3 -2 )
MRIreorder() -----------
xdim=1 ydim=3 zdim=-2
src 131 241 99, 0.250000 0.250000 0.250000
dst 131 99 241, 0.250000 0.250000 0.250000
Determinant after swap : 0.015625
Mov: (0.25, 0.25, 0.25)mm and dim (131, 99, 241)
Dst: (1, 1, 1)mm and dim (38, 43, 57)
Asserting both images: 1mm isotropic
- reslicing Mov ...
-- changing data type from 4 to 3 (noscale = 0)...
-- Original : (0.25, 0.25, 0.25)mm and (131, 99, 241) voxels.
-- Resampled: (1, 1, 1)mm and (38, 43, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
- reslicing Dst ...
-- Original : (1, 1, 1)mm and (38, 43, 57) voxels.
-- Resampled: (1, 1, 1)mm and (38, 43, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
Registration::computeMultiresRegistration
- computing centroids
- computing initial transform
-- using translation info
- Get Gaussian Pyramid Limits ( min size: 16 max size: -1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- initial transform:
Ti = [ ...
1.0000000000000 0 0 0.1781192630761
0 1.0000000000000 0 1.0539982530706
0 0 1.0000000000000 -3.1974090629449
0 0 0 1.0000000000000 ]
- initial iscale: Ii =1
Resolution: 1 S( 19 21 30 ) T( 19 21 30 )
Iteration(f): 1
-- diff. to prev. transform: 13.2959
Iteration(f): 2
-- diff. to prev. transform: 9.20966
Iteration(f): 3
-- diff. to prev. transform: 6.22883
Iteration(f): 4
-- diff. to prev. transform: 8.12577
Iteration(f): 5
-- diff. to prev. transform: 6.11784 max it: 5 reached!
Resolution: 0 S( 38 43 61 ) T( 38 43 61 )
Iteration(f): 1
-- diff. to prev. transform: 5.83495
Iteration(f): 2
-- diff. to prev. transform: 1.34307
Iteration(f): 3
-- diff. to prev. transform: 0.589867
Iteration(f): 4
-- diff. to prev. transform: 0.289573
Iteration(f): 5
-- diff. to prev. transform: 0.137676 max it: 5 reached!
- final transform:
Tf = [ ...
0.9980802661280 -0.0059694736544 0.0616453384301 -1.7131111872539
-0.0239991870640 0.8803011391816 0.4738079182283 -13.5066607583463
-0.0570948455303 -0.4743777711274 0.8784679327523 13.0909553444701
0 0 0 1.0000000000000 ]
- final iscale: If = 1
**********************************************************
*
* WARNING: Registration did not converge in 5 steps!
* Problem might be ill posed.
* Please inspect output manually!
*
**********************************************************
Final Transform:
Adjusting final transform due to initial resampling (voxel or size changes)
...
M = [ ...
0.2495200665320 0.0154113346075 0.0014923684136 0.7292410424572
-0.0059997967660 0.1184519795571 -0.2200752847954 16.2081470043947
-0.0142737113826 0.2196169831881 0.1185944427819 -4.6804480513511
0 0 0 1.0000000000000 ]
Determinant : 0.015625
writing output transformation to trash.lta ...
converting VOX to RAS and saving RAS2RAS...
mapmovhdr: Changing vox2ras MOV header (to map to DST) ...
To check aligned result, run:
freeview -v /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz
imageDump_coregistered.mgz
Registration took 0 minutes and 1 seconds.
Thank you for using RobustRegister!
If you find it useful and use it for a publication, please cite:
Highly Accurate Inverse Consistent Registration: A Robust Approach
M. Reuter, H.D. Rosas, B. Fischl. NeuroImage 53(4):1181-1196, 2010.
http://dx.doi.org/10.1016/j.neuroimage.2010.07.020
http://reuter.mit.edu/papers/reuter-robreg10.pdf
$Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $
--mov: Using imageDump.mgz as movable/source volume.
--dst: Using /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz
as target volume.
--lta: Output transform as trash.lta .
--mapmovhdr: Will save header adjusted movable as
imageDump_coregistered.mgz !
--affine: Enableing affine transform!
--sat: Using saturation 50 in M-estimator!
reading source 'imageDump.mgz'...
reading target '/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz'.
..
Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )
Type Source : 4 Type Target : 3 ensure both FLOAT (3)
Reordering axes in mov to better fit dst... ( 1 3 -2 )
MRIreorder() -----------
xdim=1 ydim=3 zdim=-2
src 131 241 99, 0.250000 0.250000 0.250000
dst 131 99 241, 0.250000 0.250000 0.250000
Determinant after swap : 0.015625
Mov: (0.25, 0.25, 0.25)mm and dim (131, 99, 241)
Dst: (1, 1, 1)mm and dim (38, 43, 57)
Asserting both images: 1mm isotropic
- reslicing Mov ...
-- changing data type from 4 to 3 (noscale = 0)...
-- Original : (0.25, 0.25, 0.25)mm and (131, 99, 241) voxels.
-- Resampled: (1, 1, 1)mm and (38, 43, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
- reslicing Dst ...
-- Original : (1, 1, 1)mm and (38, 43, 57) voxels.
-- Resampled: (1, 1, 1)mm and (38, 43, 61) voxels.
-- Reslicing using cubic bspline
MRItoBSpline degree 3
Registration::computeMultiresRegistration
- computing centroids
- computing initial transform
-- using translation info
- Get Gaussian Pyramid Limits ( min size: 16 max size: -1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )
- initial transform:
Ti = [ ...
1.0000000000000 0 0 0.1781175809123
0 1.0000000000000 0 1.0539986543476
0 0 1.0000000000000 -3.1974083471847
0 0 0 1.0000000000000 ]
- initial iscale: Ii =1
Resolution: 1 S( 19 21 30 ) T( 19 21 30 )
Iteration(f): 1
-- diff. to prev. transform: 9.84742
Iteration(f): 2
-- diff. to prev. transform: 7.72517
Iteration(f): 3
-- diff. to prev. transform: 8.94618
Iteration(f): 4
-- diff. to prev. transform: 7.30294
Iteration(f): 5
-- diff. to prev. transform: 5.69484 max it: 5 reached!
Resolution: 0 S( 38 43 61 ) T( 38 43 61 )
Iteration(f): 1
-- diff. to prev. transform: 11.7013
Iteration(f): 2
-- diff. to prev. transform: 3.26787
Iteration(f): 3
-- diff. to prev. transform: 1.06278
Iteration(f): 4
-- diff. to prev. transform: 0.347277
Iteration(f): 5
-- diff. to prev. transform: 0.0826464 max it: 5 reached!
- final transform:
Tf = [ ...
1.1636664104160 -0.3014738824441 0.0004403516595 4.0520187720971
-0.0480158583329 1.0596278475093 0.4954259490783 -17.9010148715481
-0.2453688431946 -0.4779665918288 0.8802303084621 16.7816318160186
0 0 0 1.0000000000000 ]
- final iscale: If = 1
**********************************************************
*
* WARNING: Registration did not converge in 5 steps!
* Problem might be ill posed.
* Please inspect output manually!
*
**********************************************************
Final Transform:
Adjusting final transform due to initial resampling (voxel or size changes)
...
M = [ ...
0.2909164812245 0.0001100842157 0.0753684565922 -3.0302464159984
-0.0120039592287 0.1238564808785 -0.2649069144859 17.7887142169889
-0.0613421845898 0.2200575304725 0.1194916267047 -1.6040021052477
0 0 0 1.0000000000000 ]
Determinant : 0.0216399
Decompose into Rot * Shear * Scale :
Rot = [ ...
0.9808313831675 0.1119800663090 0.1594686882846
0.0897438323260 0.4668219029177 -0.8797859714247
-0.1729619679387 0.8772330224665 0.4478240524369 ]
Shear = [ ...
1.0000000000000 -0.1069794540990 0.0987385001868
-0.0910164402411 1.0000000000000 -0.0348388469911
0.0999837864599 -0.0414655431721 1.0000000000000 ]
Scale = diag([ 0.2948725983257 0.2508729779031 0.2985915205121 ])
writing output transformation to trash.lta ...
converting VOX to RAS and saving RAS2RAS...
mapmovhdr: Changing vox2ras MOV header (to map to DST) ...
To check aligned result, run:
freeview -v /mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right//hippoAmygBinaryMask_autoCropped.mgz
imageDump_coregistered.mgz
Registration took 0 minutes and 1 seconds.
Thank you for using RobustRegister!
If you find it useful and use it for a publication, please cite:
Highly Accurate Inverse Consistent Registration: A Robust Approach
M. Reuter, H.D. Rosas, B. Fischl. NeuroImage 53(4):1181-1196, 2010.
http://dx.doi.org/10.1016/j.neuroimage.2010.07.020
http://reuter.mit.edu/papers/reuter-robreg10.pdf
Reading contexts of file
/usr/local/packages/freesurfer_v6.0.0/average/HippoSF/atlas/compressionLookupTable.txt
Constructing image-to-world transform from header information (asegMod.mgz)
Returning the following transform:
AffineTransform (0x2b82ee48f820)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 422
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Offset: [132.04, -111.801, 144.75]
Center: [0, 0, 0]
Translation: [132.04, -111.801, 144.75]
Inverse:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Singular: 0
Constructing image-to-world transform from header information
(/mnt/BIAC/.users/ch186/
duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_right/imageDump.mgz
)
Returning the following transform:
AffineTransform (0x2b82ee48f820)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 579
Debug: Off
Object Name:
Observers:
none
Matrix:
-0.290916 -0.000110086 -0.0753684
-0.0613422 0.220058 0.119492
0.012004 -0.123856 0.264907
Offset: [49.0706, -22.4049, 0.96176]
Center: [0, 0, 0]
Translation: [49.0706, -22.4049, 0.96176]
Inverse:
-3.37777 -0.432721 -0.765819
-0.81721 3.51948 -1.82003
-0.229025 1.66513 2.95866
Singular: 0
Transform before cropping:
AffineTransform (0x2b82ee48f820)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 581
Debug: Off
Object Name:
Observers:
none
Matrix:
0.290916 0.000110086 0.0753685
-0.012004 0.123856 -0.264907
-0.0613422 0.220058 0.119492
Offset: [82.9698, 143.789, 89.396]
Center: [0, 0, 0]
Translation: [82.9698, 143.789, 89.396]
Inverse:
3.37777 0.765819 -0.432721
0.81721 1.82003 3.51948
0.229025 -2.95866 1.66513
Singular: 0
WorldToImageTransform before cropping:
AffineTransform (0x2b82ec807bf0)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 583
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Offset: [132.04, 144.75, 111.801]
Center: [0, 0, 0]
Translation: [132.04, 144.75, 111.801]
Inverse:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Singular: 0
m_BoundingBoxSize: [131, 241,99]
minimalMappedCoordinate: [82.9698, 116.267,81.4215]
maximalMappedCoordinate: [128.201, 173.514,153.92]
Cropping with min [78 111 74]
and max [133 179 161]
m_OriginalImageRegion before checking margins: ImageRegion (0x2b82ec809218)
Dimension: 3
Index: [78, 111, 74]
Size: [56, 69, 88]
m_CroppedImageRegion before checking margins: ImageRegion (0x2b82ec8091e0)
Dimension: 3
Index: [0, 0, 0]
Size: [56, 69, 88]
m_OriginalImageRegion after checking margins: ImageRegion (0x2b82ec809218)
Dimension: 3
Index: [78, 111, 74]
Size: [56, 69, 88]
m_CroppedImageRegion after checking margins: ImageRegion (0x2b82ec8091e0)
Dimension: 3
Index: [0, 0, 0]
Size: [56, 69, 88]
Transform after cropping:
AffineTransform (0x2b82ee48f820)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 740
Debug: Off
Object Name:
Observers:
none
Matrix:
0.290916 0.000110086 0.0753685
-0.012004 0.123856 -0.264907
-0.0613422 0.220058 0.119492
Offset: [4.96976, 32.7887, 15.396]
Center: [0, 0, 0]
Translation: [4.96976, 32.7887, 15.396]
Inverse:
3.37777 0.765819 -0.432721
0.81721 1.82003 3.51948
0.229025 -2.95866 1.66513
Singular: 0
WorldToImageTransform after cropping:
AffineTransform (0x2b82ec807bf0)
RTTI typeinfo: itk::AffineTransform<double, 3u>
Reference Count: 1
Modified Time: 741
Debug: Off
Object Name:
Observers:
none
Matrix:
-1 1.3024e-09 1.86265e-09
-1.86265e-09 -1.16415e-10 -1
-3.49428e-09 1 -1.16415e-10
Offset: [54.0404, 33.7505, 37.8009]
Center: [0, 0, 0]
Translation: [54.0404, 33.7505, 37.8009]
Inverse:
-1 -1.86265e-09 1.3024e-09
-3.49428e-09 -1.16415e-10 1
1.86265e-09 -1 -1.16415e-10
Singular: 0
Transforming points
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Warning: This concatenation operation includes an empty array with an
incorrect number of rows.
Concatenation including empty arrays will require all arrays to have the
same number of rows in a future release.
[ > In segmentSubjectT1_autoEstimateAlveusML at 325]
Reading contexts of file
/usr/local/packages/freesurfer_v6.0.0/average/HippoSF/atlas/compressionLookupTable.txt
--------------
Making Lateral-nucleus map to reduced label 1
Making Paralaminar-nucleus map to reduced label 1
Making Basal-nucleus map to reduced label 1
Making Accessory-Basal-nucleus map to reduced label 1
Making Corticoamygdaloid-transitio map to reduced label 1
Making Central-nucleus map to reduced label 1
Making Cortical-nucleus map to reduced label 1
Making Medial-nucleus map to reduced label 1
Making Anterior-amygdaloid-area-AAA map to reduced label 1
--------------
Making alveus map to reduced label 2
Making Hippocampal_tail map to reduced label 2
Making HATA map to reduced label 2
Making fimbria map to reduced label 2
Making parasubiculum map to reduced label 2
Making hippocampal-fissure map to reduced label 2
--------------
Making Left-Cerebral-Cortex map to reduced label 3
--------------
Making Left-Cerebral-White-Matter map to reduced label 4
--------------
Making Left-Lateral-Ventricle map to reduced label 5
--------------
Making Left-choroid-plexus map to reduced label 6
--------------
Making Unknown map to reduced label 7
--------------
Making Left-VentralDC map to reduced label 8
--------------
Making Left-Putamen map to reduced label 9
--------------
Making Left-Pallidum map to reduced label 10
--------------
Making Left-Thalamus-Proper map to reduced label 11
--------------
Making Left-Accumbens-area map to reduced label 12
--------------
Making Left-Caudate map to reduced label 13
Error using segmentSubjectT1_autoEstimateAlveusML (line 348)
The vector of prior probabilities in the mesh nodes must always sum to one
over all classes