Not sure what is happending from the log file. Can you run it outside of recon-all?
On 8/26/2020 11:23 AM, Emily K Clarke wrote:
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 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 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 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
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