Hi Emily.
Is it possibly that you may be mixing FS versions, by any chance?
Cheers,
/Eugenio
Juan Eugenio Iglesias
Senior research fellow
CMIC (UCL), MGH (HMS) and CSAIL (MIT)
From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Emily K Clarke <ekc23@duke.edu>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Wednesday, September 9, 2020 at 15:53
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] Hippocampal subfields error
External Email - Use Caution
Hi Eugenio,
We’re still running into the issue where running recon-all with the hippocampal subfields tag isn’t actually generating any of the hippocampal files. I’ve included our full recon-all log below. We already examined the scans, and they look
perfectly normal – do you know why this might be happening?
Thanks,
Emily Clarke-Rubright
Morey Neuroimaging Lab
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
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
Transforming points
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