External Email - Use Caution Dear Juan Eugenio, thanks for your answer. I tried to do with the corrected images and wit the raw ones (before the correction), and I got the same error. Then I tried with two patients more and happened the same. I don´t know if it is due to the dev version we used, because the first time it worked very well. Best regards, JC.
El dom., 13 oct. 2019 a las 12:01, <freesurfer-requ...@nmr.mgh.harvard.edu> escribió: > Send Freesurfer mailing list submissions to > freesurfer@nmr.mgh.harvard.edu > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > or, via email, send a message with subject or body 'help' to > freesurfer-requ...@nmr.mgh.harvard.edu > > You can reach the person managing the list at > freesurfer-ow...@nmr.mgh.harvard.edu > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Freesurfer digest..." > > > Today's Topics: > > 1. HippoAmyg (Juan Rivas) > 2. Learning dti processing tutorial (Renew Andrade) > 3. Re: HippoAmyg (Iglesias Gonzalez, Juan E.) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 12 Oct 2019 16:02:28 -0400 > From: Juan Rivas <jcr...@gmail.com> > Subject: [Freesurfer] HippoAmyg > To: freesurfer@nmr.mgh.harvard.edu > Message-ID: > <CACYE61CZSKt0p-q= > k+yph1ddvpw4o67qehmxfhvpem7gqob...@mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > External Email - Use Caution > > *Hi, I runned the reconall of my images with FS60 with this command:* > > *shiraz[0]:NIFTI$ recon-all -i > > /autofs/cluster/neuromod/rivas/imagenes/NIFTI/sub-esq-02-en/anat/sub-esq-02-en_T1w.nii.gz > -s /autofs/cluster/neuromod/rivas/subject-esq-02-en. There were no errors.* > > *Then I runned recon for hippocampus and amygdala with fsdev on Thu Aug 22 > 15:36:32 , with this command:* > > *segmentHA_T1.sh* > > *There were no errors. Then I identified and corrected manually the errors > on the FS60 images.* > > *Then I run recon-all on fs60 without to touch hippo-amyg.* > > *Now, I am trying to make the hippo-amyg correction with this command:* > > *segmentHA_T1.sh on fsdev, and I got this error:* > > > > [shiraz:FS] (nmr-dev-env) segmentHA_T1.sh test1 > > #-------------------------------------------- > > #@# Hippocampal Subfields processing (T1) left Fri Oct 11 17:20:27 EDT 2019 > > /usr/bin/time -o /dev/stdout > > @#@FSTIME 2019:10:11:17:20:27 run_segmentSubjectT1_autoEstimateAlveusML.sh > N 13 e %e S %S U %U P %P M %M F %F R %R W %W c %c w %w I %I O %O L 1.23 > 1.35 1.67 > > run_segmentSubjectT1_autoEstimateAlveusML.sh > /usr/local/freesurfer/dev/MCRv84/ test1 /cluster/neuromod/rivas/imagenes/FS > 0.333333333333333333333333333333333333 > /usr/local/freesurfer/dev/average/HippoSF/atlas/AtlasMesh.gz > /usr/local/freesurfer/dev/average/HippoSF/atlas/AtlasDump.mgz > /usr/local/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > 0.05 left L-BFGS v21 /usr/local/freesurfer/dev/bin/ 0 > > ------------------------------------------ > > Setting up environment variables > > --- > > LD_LIBRARY_PATH is > > .:/lib64:/usr/local/freesurfer/dev/MCRv84//runtime/glnxa64:/usr/local/freesurfer/dev/MCRv84//bin/glnxa64:/usr/local/freesurfer/dev/MCRv84//sys/os/glnxa64:/native_threads:/server:/client:: > > Registering imageDump.mgz to hippocampal mask from ASEG > > $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 > > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 > > '/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 ) > > 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 (37, 33, 61) > > 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 (37, 33, 61) voxels. > > -- Reslicing using cubic bspline > > MRItoBSpline degree 3 > > - no Dst reslice necessary > > > > > > 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: 0 ) > > - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 0 ) > > - initial transform: > > Ti = [ ... > > 1.0000000000000 0 0 -0.9335110261151 > > 0 1.0000000000000 0 -0.6030053897425 > > 0 0 1.0000000000000 -1.9033167008449 > > 0 0 0 1.0000000000000 ] > > > > - initial iscale: Ii =1 > > > > Resolution: 0 S( 37 33 61 ) T( 37 33 61 ) > > Iteration(f): 1 > > -- diff. to prev. transform: 17.9258 > > Iteration(f): 2 > > -- diff. to prev. transform: 13.3727 > > Iteration(f): 3 > > -- diff. to prev. transform: 12.6349 > > Iteration(f): 4 > > -- diff. to prev. transform: 0.963353 > > Iteration(f): 5 > > -- diff. to prev. transform: 0.23376 max it: 5 reached! > > > > - final transform: > > Tf = [ ... > > 0.9994502743718 -0.0309610775894 -0.0118558311665 0.1083605389283 > > 0.0330356012422 0.9601637341023 0.2774783825190 -11.0026122646332 > > 0.0027925093931 -0.2777175100517 0.9606587253036 3.8161835807274 > > 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 = [ ... > > -0.2498625685929 -0.0029639577916 0.0077402693973 33.8236195063683 > > -0.0082589003105 0.0693695956298 -0.2400409335256 17.7299867104994 > > -0.0006981273483 0.2401646813259 0.0694293775129 -3.6765424847757 > > 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 > > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 > > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_left//hippoAmygBinaryMask_autoCropped.mgz > as target volume. > > --lta: Output transform as trash.lta . > > --mapmovhdr: Will save header adjusted movable as > imageDump_coregistered.mgz ! > > --affine: Enabling affine transform! > > --sat: Using saturation 50 in M-estimator! > > > > reading source 'imageDump.mgz'... > > reading target > > '/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 ) > > 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 (37, 33, 61) > > 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 (37, 33, 61) voxels. > > -- Reslicing using cubic bspline > > MRItoBSpline degree 3 > > - no Dst reslice necessary > > > > > > 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: 0 ) > > - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 0 ) > > - initial transform: > > Ti = [ ... > > 1.0000000000000 0 0 -0.9335121201217 > > 0 1.0000000000000 0 -0.6030049400697 > > 0 0 1.0000000000000 -1.9033196349668 > > 0 0 0 1.0000000000000 ] > > > > - initial iscale: Ii =1 > > > > Resolution: 0 S( 37 33 61 ) T( 37 33 61 ) > > Iteration(f): 1 > > -- diff. to prev. transform: 29.7552 > > Iteration(f): 2 > > -- diff. to prev. transform: 13.9258 > > Iteration(f): 3 > > -- diff. to prev. transform: 12.8176 > > Iteration(f): 4 > > -- diff. to prev. transform: 4.31284 > > Iteration(f): 5 > > -- diff. to prev. transform: 1.08934 max it: 5 reached! > > > > - final transform: > > Tf = [ ... > > 1.1485282870250 0.1923732018210 0.0456719546813 -8.8430815689836 > > 0.0248585691740 1.1974718877709 0.2901612074595 -15.4946754855698 > > 0.0132871026014 0.0262311630292 0.9721734242629 -1.7628900186542 > > 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 = [ ... > > -0.2871321056267 0.0114179894966 -0.0480933061884 36.4485194686672 > > -0.0062146408039 0.0725403105008 -0.2993680076302 19.7524929053736 > > -0.0033217759975 0.2430433850326 -0.0065577915391 -0.1873902167255 > > 0 0 0 1.0000000000000 ] > > > > Determinant : -0.020683 > > > > Decompose into Rot * Shear * Scale : > > > > Rot = [ ... > > -0.9973893744923 0.0079822957206 -0.0717685070543 > > 0.0722067536928 0.1210866300984 -0.9900122285773 > > -0.0007876362909 0.9926098483122 0.1213468939142 ] > > > > Shear = [ ... > > 1.0000000000000 -0.0253544642652 0.0881389503515 > > -0.0221787471386 1.0000000000000 -0.1442736100723 > > 0.0921761860222 -0.1724865310828 1.0000000000000 ] > > > > Scale = diag([ 0.2859363885412 0.2501220610640 0.2990338055489 ]) > > > > > > 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 > > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > > Constructing image-to-world transform from header information > (asegModCHA.mgz) > > Constructing image-to-world transform from header information > > (/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_left/imageDump.mgz) > > 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 > > Reading contexts of file > /usr/local/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > > -------------- > > Making Left-Cerebral-Cortex map to reduced label 1 > > Making alveus map to reduced label 1 > > Making subiculum-body map to reduced label 1 > > Making subiculum-head map to reduced label 1 > > Making Hippocampal_tail map to reduced label 1 > > Making molecular_layer_HP-body map to reduced label 1 > > Making molecular_layer_HP-head map to reduced label 1 > > Making GC-ML-DG-body map to reduced label 1 > > Making GC-ML-DG-head map to reduced label 1 > > Making CA4-body map to reduced label 1 > > Making CA4-head map to reduced label 1 > > Making CA1-body map to reduced label 1 > > Making CA1-head map to reduced label 1 > > Making CA3-body map to reduced label 1 > > Making CA3-head map to reduced label 1 > > Making HATA map to reduced label 1 > > Making fimbria map to reduced label 1 > > Making presubiculum-body map to reduced label 1 > > Making presubiculum-head map to reduced label 1 > > Making parasubiculum map to reduced label 1 > > 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 Left-Cerebral-White-Matter map to reduced label 2 > > -------------- > > Making Left-Lateral-Ventricle map to reduced label 3 > > -------------- > > Making Left-choroid-plexus map to reduced label 4 > > -------------- > > Making hippocampal-fissure map to reduced label 5 > > Making Unknown map to reduced label 5 > > -------------- > > Making Left-VentralDC map to reduced label 6 > > -------------- > > Making Left-Putamen map to reduced label 7 > > -------------- > > Making Left-Pallidum map to reduced label 8 > > -------------- > > Making Left-Accumbens-area map to reduced label 9 > > -------------- > > Making Left-Caudate map to reduced label 10 > > Error using segmentSubjectT1_autoEstimateAlveusML (line 365) > > The vector of prior probabilities in the mesh nodes must always sum to one > over all classes. > > > > > How may I correct it? > > Thanks lot, > > JC. > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > http://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/attachments/20191012/28a4047a/attachment-0001.html > > ------------------------------ > > > > > ------------------------------ > > Message: 3 > Date: Sun, 13 Oct 2019 14:18:16 +0000 > From: "Iglesias Gonzalez, Juan E." <jiglesiasgonza...@mgh.harvard.edu> > Subject: Re: [Freesurfer] HippoAmyg > To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> > Message-ID: <aca11431-fd5c-45c8-a466-ffdaba5ae...@mgh.harvard.edu> > Content-Type: text/plain; charset="utf-8" > > Dear Juan, > Is this happening for a single subject, or for every subject? > Kind regards, > /Eugenio > > Juan Eugenio Iglesias > Senior research fellow > CMIC (UCL), MGH (HMS) and CSAIL (MIT) > http://www.jeiglesias.com > > > From: <freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of Juan Rivas < > jcr...@gmail.com> > Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu> > Date: Sunday, 13 October 2019 at 04:03 > To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu> > Subject: [Freesurfer] HippoAmyg > > > External Email - Use Caution > > Hi, I runned the reconall of my images with FS60 with this command: > > shiraz[0]:NIFTI$ recon-all -i > /autofs/cluster/neuromod/rivas/imagenes/NIFTI/sub-esq-02-en/anat/sub-esq-02-en_T1w.nii.gz > -s /autofs/cluster/neuromod/rivas/subject-esq-02-en. There were no errors. > > Then I runned recon for hippocampus and amygdala with fsdev on Thu Aug 22 > 15:36:32 , with this command: > > segmentHA_T1.sh > > There were no errors. Then I identified and corrected manually the errors > on the FS60 images. > > Then I run recon-all on fs60 without to touch hippo-amyg. > > Now, I am trying to make the hippo-amyg correction with this command: > > segmentHA_T1.sh on fsdev, and I got this error: > > > > [shiraz:FS] (nmr-dev-env) segmentHA_T1.sh test1 > > #-------------------------------------------- > > #@# Hippocampal Subfields processing (T1) left Fri Oct 11 17:20:27 EDT 2019 > > /usr/bin/time -o /dev/stdout > > @#@FSTIME 2019:10:11:17:20:27 run_segmentSubjectT1_autoEstimateAlveusML.sh > N 13 e %e S %S U %U P %P M %M F %F R %R W %W c %c w %w I %I O %O L 1.23 > 1.35 1.67 > > run_segmentSubjectT1_autoEstimateAlveusML.sh > /usr/local/freesurfer/dev/MCRv84/ test1 /cluster/neuromod/rivas/imagenes/FS > 0.333333333333333333333333333333333333 > /usr/local/freesurfer/dev/average/HippoSF/atlas/AtlasMesh.gz > /usr/local/freesurfer/dev/average/HippoSF/atlas/AtlasDump.mgz > /usr/local/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > 0.05 left L-BFGS v21 /usr/local/freesurfer/dev/bin/ 0 > > ------------------------------------------ > > Setting up environment variables > > --- > > LD_LIBRARY_PATH is > .:/lib64:/usr/local/freesurfer/dev/MCRv84//runtime/glnxa64:/usr/local/freesurfer/dev/MCRv84//bin/glnxa64:/usr/local/freesurfer/dev/MCRv84//sys/os/glnxa64:/native_threads:/server:/client:: > > Registering imageDump.mgz to hippocampal mask from ASEG > > $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 > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 > '/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 ) > > 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 (37, 33, 61) > > 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 (37, 33, 61) voxels. > > -- Reslicing using cubic bspline > > MRItoBSpline degree 3 > > - no Dst reslice necessary > > > > > > 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: 0 ) > > - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 0 ) > > - initial transform: > > Ti = [ ... > > 1.0000000000000 0 0 -0.9335110261151 > > 0 1.0000000000000 0 -0.6030053897425 > > 0 0 1.0000000000000 -1.9033167008449 > > 0 0 0 1.0000000000000 ] > > > > - initial iscale: Ii =1 > > > > Resolution: 0 S( 37 33 61 ) T( 37 33 61 ) > > Iteration(f): 1 > > -- diff. to prev. transform: 17.9258 > > Iteration(f): 2 > > -- diff. to prev. transform: 13.3727 > > Iteration(f): 3 > > -- diff. to prev. transform: 12.6349 > > Iteration(f): 4 > > -- diff. to prev. transform: 0.963353 > > Iteration(f): 5 > > -- diff. to prev. transform: 0.23376 max it: 5 reached! > > > > - final transform: > > Tf = [ ... > > 0.9994502743718 -0.0309610775894 -0.0118558311665 0.1083605389283 > > 0.0330356012422 0.9601637341023 0.2774783825190 -11.0026122646332 > > 0.0027925093931 -0.2777175100517 0.9606587253036 3.8161835807274 > > 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 = [ ... > > -0.2498625685929 -0.0029639577916 0.0077402693973 33.8236195063683 > > -0.0082589003105 0.0693695956298 -0.2400409335256 17.7299867104994 > > -0.0006981273483 0.2401646813259 0.0694293775129 -3.6765424847757 > > 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 > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_left//hippoAmygBinaryMask_autoCropped.mgz > as target volume. > > --lta: Output transform as trash.lta . > > --mapmovhdr: Will save header adjusted movable as > imageDump_coregistered.mgz ! > > --affine: Enabling affine transform! > > --sat: Using saturation 50 in M-estimator! > > > > reading source 'imageDump.mgz'... > > reading target > '/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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 ) > > 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 (37, 33, 61) > > 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 (37, 33, 61) voxels. > > -- Reslicing using cubic bspline > > MRItoBSpline degree 3 > > - no Dst reslice necessary > > > > > > 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: 0 ) > > - Build Gaussian Pyramid ( Limits min steps: 0 max steps: 0 ) > > - initial transform: > > Ti = [ ... > > 1.0000000000000 0 0 -0.9335121201217 > > 0 1.0000000000000 0 -0.6030049400697 > > 0 0 1.0000000000000 -1.9033196349668 > > 0 0 0 1.0000000000000 ] > > > > - initial iscale: Ii =1 > > > > Resolution: 0 S( 37 33 61 ) T( 37 33 61 ) > > Iteration(f): 1 > > -- diff. to prev. transform: 29.7552 > > Iteration(f): 2 > > -- diff. to prev. transform: 13.9258 > > Iteration(f): 3 > > -- diff. to prev. transform: 12.8176 > > Iteration(f): 4 > > -- diff. to prev. transform: 4.31284 > > Iteration(f): 5 > > -- diff. to prev. transform: 1.08934 max it: 5 reached! > > > > - final transform: > > Tf = [ ... > > 1.1485282870250 0.1923732018210 0.0456719546813 -8.8430815689836 > > 0.0248585691740 1.1974718877709 0.2901612074595 -15.4946754855698 > > 0.0132871026014 0.0262311630292 0.9721734242629 -1.7628900186542 > > 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 = [ ... > > -0.2871321056267 0.0114179894966 -0.0480933061884 36.4485194686672 > > -0.0062146408039 0.0725403105008 -0.2993680076302 19.7524929053736 > > -0.0033217759975 0.2430433850326 -0.0065577915391 -0.1873902167255 > > 0 0 0 1.0000000000000 ] > > > > Determinant : -0.020683 > > > > Decompose into Rot * Shear * Scale : > > > > Rot = [ ... > > -0.9973893744923 0.0079822957206 -0.0717685070543 > > 0.0722067536928 0.1210866300984 -0.9900122285773 > > -0.0007876362909 0.9926098483122 0.1213468939142 ] > > > > Shear = [ ... > > 1.0000000000000 -0.0253544642652 0.0881389503515 > > -0.0221787471386 1.0000000000000 -0.1442736100723 > > 0.0921761860222 -0.1724865310828 1.0000000000000 ] > > > > Scale = diag([ 0.2859363885412 0.2501220610640 0.2990338055489 ]) > > > > > > 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 > /cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_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/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > > Constructing image-to-world transform from header information > (asegModCHA.mgz) > > Constructing image-to-world transform from header information > (/cluster/neuromod/rivas/imagenes/FS/test1/tmp/hippoSF_T1_v21_left/imageDump.mgz) > > 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 > > Reading contexts of file > /usr/local/freesurfer/dev/average/HippoSF/atlas/compressionLookupTable.txt > > -------------- > > Making Left-Cerebral-Cortex map to reduced label 1 > > Making alveus map to reduced label 1 > > Making subiculum-body map to reduced label 1 > > Making subiculum-head map to reduced label 1 > > Making Hippocampal_tail map to reduced label 1 > > Making molecular_layer_HP-body map to reduced label 1 > > Making molecular_layer_HP-head map to reduced label 1 > > Making GC-ML-DG-body map to reduced label 1 > > Making GC-ML-DG-head map to reduced label 1 > > Making CA4-body map to reduced label 1 > > Making CA4-head map to reduced label 1 > > Making CA1-body map to reduced label 1 > > Making CA1-head map to reduced label 1 > > Making CA3-body map to reduced label 1 > > Making CA3-head map to reduced label 1 > > Making HATA map to reduced label 1 > > Making fimbria map to reduced label 1 > > Making presubiculum-body map to reduced label 1 > > Making presubiculum-head map to reduced label 1 > > Making parasubiculum map to reduced label 1 > > 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 Left-Cerebral-White-Matter map to reduced label 2 > > -------------- > > Making Left-Lateral-Ventricle map to reduced label 3 > > -------------- > > Making Left-choroid-plexus map to reduced label 4 > > -------------- > > Making hippocampal-fissure map to reduced label 5 > > Making Unknown map to reduced label 5 > > -------------- > > Making Left-VentralDC map to reduced label 6 > > -------------- > > Making Left-Putamen map to reduced label 7 > > -------------- > > Making Left-Pallidum map to reduced label 8 > > -------------- > > Making Left-Accumbens-area map to reduced label 9 > > -------------- > > Making Left-Caudate map to reduced label 10 > > Error using segmentSubjectT1_autoEstimateAlveusML (line 365) > > The vector of prior probabilities in the mesh nodes must always sum to one > over all classes. > > > > > > > > How may I correct it? > > Thanks lot, > > JC. > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > http://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/attachments/20191013/5cda0e71/attachment-0001.html > > ------------------------------ > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > End of Freesurfer Digest, Vol 188, Issue 21 > ******************************************* >
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