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Re: [Freesurfer] Freesurfer Digest, Vol 188, Issue 21
by Juan Rivas 13 Oct '19

13 Oct '19

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-request(a)nmr.mgh.harvard.edu> escribió: > Send Freesurfer mailing list submissions to > freesurfer(a)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-request(a)nmr.mgh.harvard.edu > > You can reach the person managing the list at > freesurfer-owner(a)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 <jcrn12(a)gmail.com> > Subject: [Freesurfer] HippoAmyg > To: freesurfer(a)nmr.mgh.harvard.edu > Message-ID: > <CACYE61CZSKt0p-q= > k+Yph1dDvpW4O67qehmXfhVpem7gqobdUg(a)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. >

1 0

HippoAmyg
by Juan Rivas 13 Oct '19

13 Oct '19

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.

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TRACULA prep gets stuck in -prior 'WARN: Could not find satisfactory control point fit - try 20784 Finding center streamline'
by Mazzetti, C. (Cecilia) 11 Oct '19

11 Oct '19

External Email - Use Caution Dear all, I am trying to understand what is going on in my subjects (same problem with 5 different ones). the outputs from the first steps of trac-all seems to work fine, so I am running: trac-all -prep -c config_01C.txt -nocorr -noqa -nointra -nointer -nomasks -notensor -no-isrunning but the process gets stuck (in the log file I read something like 'WARN: Could not find satisfactory control point fit - try 20784 Finding center streamline' ) which keeps going... The only outputs which seem to be created are for cst and Ilf, the others not. I am also trying to include just some tract by specifying in the configuration file: set pathlist = ( lh.slfp_PP rh.slfp_PP \ lh.slft_PP rh.slft_PP ) but nothing seems to change.. Can I please have some assistance here? It has been days and I cannot seem to fix it.. also, I tried to run bedpost only but I receive an erro: trac-all -prep -c config_01C.txt -nocorr -noqa -nointra -nointer -nomasks -notensor -noprior -no-isrunning saying that I didn't specify any steps.. isn't bedpost a preprocessing step? also when tryingtrac-all -bedp -c config_02C.txt -no-isrunning? nothing works... is it because the -prior steps needs to be finished? Thanks to anyone willing to help! Best, Cecilia Cecilia Mazzetti - Ph.D. Researcher Donders Centre for Cognitive Neuroimaging, room 2.257 Kapittelweg 29 | 6525 EN Nijmegen

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Re: [Freesurfer] ERROR gtmseg
by Marina Fernández 11 Oct '19

11 Oct '19

External Email - Use Caution Dear Douglas, Thank you very much for the help. We could solve the problem with that subject but now we have a similar problem with another subject. In the previous case, we have only one problematic voxel in the skull, but now the label 75 (it shouldn't exist either) is taking a lot of voxels in the ventricles and the caudate. So, I think that we should use other solution to fix it. I know that this issue is weird. We use gtmseg command with more or less 500 subjects and we only have this type of problem with two subjects. Best regards, Marina. > Probably the easiest thing is just to edit that voxel to be one of the neighboring > segments. First, load the aseg and find that voxel. See which segment(s) are around > that voxel and get the segmentation id. Then run > mri_binarize --replaceonly 229 YourNewSegID --i aparc+aseg.mgz --o > aparc+aseg.mgz > then re-run gtmseg

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Re: [Freesurfer] ERROR gtmseg
by Marina Fernández 11 Oct '19

11 Oct '19

2 1

Freesurfer using dof9 with preproc-sess
by Droppa, Kyle Salmon 11 Oct '19

11 Oct '19

Good evening, I am using freesurfer version 6 and I am having an issue with changing the degrees of freedom when I run preproc-sess. I ade some registrations that are 9 and 12 dof instead of the default 6, however when I try to run preproc-sess, it pulls the dof6 files instead. Is there a flag I can use that pulls the register.dof9.lta and register.dof12.lta files instead? Thank you and have a nice night! ___________________ Kyle Salmon Droppa, B.A. Clinical Research Coordinator Athinoula A. Martinos Center for Biomedical Imaging Magnetic Resonance - Physics & Instrumentation Group https://www.martinos.org/lab/mr-pig <https://www.massgeneral.org/nicc>

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using dof9 or dof12 in preproc-sess
by Droppa, Kyle Salmon 11 Oct '19

11 Oct '19

Hello, I posted this earlier and wasn't able to get a response. I am using freesurfer version 6 and I am having an issue with changing the degrees of freedom when I run preproc-sess. I made some registrations that are 9 and 12 dof instead of the default 6 using bbregister, however when I try to run preproc-sess, it pulls the dof6 files instead. Is there a flag I can use that makes preproc use the register.dof9.lta and register.dof12.lta files instead? Thank you and have a nice day!

2 1

local Gyrification Index
by LOSKE, PHILIPP (PGR) 11 Oct '19

11 Oct '19

External Email - Use Caution Hello FreeSurfer Team, I am trying to compute the local Gyrification index on my subjects with recon-all -s <subj> -localGI. Running this under FS 6.0 runs without errors, with FS 5.3. I get: mesh_outer = struct with fields: vertices: [68598x3 double] faces: [137192x3 double] facesOfVertex: [68598x1 struct] preparing pial mesh structure ... ...searching for mesh edges...done (82.56 sec). ... creating path file for vertex 1 / 68598 area file for outer ROIs saved at 1 {Unable to perform assignment because the left and right sides have a different number of elements. Error in dsearchn (line 84) [d(i),t(i)] = min(sum((x-yi).^2,2)); Error in mesh_vertex_nearest (line 29) nearestIndex = dsearchn(vertices,points); Error in reorganize_verticeslist (line 28) [nextindex,nextvalue]=mesh_vertex_nearest(mesh_total.vertices(remaininglist,:),mesh_total.vertices(verticeslist(start_vertex),:)); Error in make_roi_paths (line 93) reorglist = reorganize_verticeslist (mesh_total, A, mesh_outer, perim, verticeslist, step); } >> ERROR: make_roi_paths did not complete successfully! Now I wonder why the computation works in version 6 but not in 5.3. My subjects are originally reconstructed with version 5.3., does the computation for local Gyrification Index differ between both versions or can I just run the command in FS6? Cheers Philipp The University of Aberdeen is a charity registered in Scotland, No SC013683. Tha Oilthigh Obar Dheathain na charthannas clàraichte ann an Alba, Àir. SC013683.

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fsaverage label into functional space
by Lauri Tuominen 10 Oct '19

10 Oct '19

External Email - Use Caution Dear FreeSurfers! I would like to confirm something before I proceed with my analyses. I think I am just confused again. I am doing resting state analysis using fsfast. I am trying to use a label defined in the fsaverage space as a seed using the fcseed-config & fcseed-sess commands. Now these commands say that the label should be in fuctional space, which I gather is the space of the f.nii. So in order to move the label into functional space I say: mri_label2vol --subject fsaverage --label lh.mylabel.in-fsaverage.label --o lh.mylabel.individualized.in-functional.mgz --proj frac 0 1 0.01 --hemi lh --temp ${projectdir}/${sessionj}/rest/001/f.nii --fill-ribbon --reg ${projectdir}/${session}/rest/register.dof6.lta To my surprise, the voxel size here corresponds to the anatomical (orig.mgz) but not the functional space (f.nii). To test this further I did: mri_label2vol --subject fsaverage --label lh.mylabel.in-fsaverage.label --o lh.mylabel.individualized.in-functional.mgz --proj frac 0 1 0.01 --hemi lh --temp $SUBJECTS_DIR/$/${sessionj}/mri/orig.mgz --fill-ribbon --reg ${projectdir}/${session}/rest/register.dof6.lta And I get exactly the same ROI in the volume. So just to confirm, is this what I want for the fcseed -commands? Thank you so much again! Lauri Tuominen

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Brodmann area parcellation
by sang ho shin 10 Oct '19

10 Oct '19

External Email - Use Caution Dear Freesurfer Developers, I am trying to get the seed mask of premotor and motor cortex. Because I can't get it through 'recon-all -all', I tried to find brodmann area ('recon-all -s subjid -ba-labels') But I received ERROR message. Can you tell me how to get Brodmann area through recon-all or freesurfer parcellation? And I appreciate if you can help me to solve this error message as follows, ================================================================= sinsanghoui-MBP:~ shinsangho$ export SUBJECTS_DIR=~/freesurfer_subjects sinsanghoui-MBP:~ shinsangho$ echo $SUBJECTS_DIR *sinsanghoui-MBP:~ shinsangho$ recon-all -s NOR82_PJI -i ~/DTI_analysis/nor82_pji_t1/coT1.nii -ba-labels* Subject Stamp: freesurfer-Darwin-OSX-stable-pub-v6.0.0-2beb96c Current Stamp: freesurfer-Darwin-OSX-stable-pub-v6.0.0-2beb96c INFO: SUBJECTS_DIR is /Users/shinsangho/freesurfer_subjects Actual FREESURFER_HOME /Applications/freesurfer Darwin sinsanghoui-MBP 15.6.0 Darwin Kernel Version 15.6.0: Thu Jun 23 18:25:34 PDT 2016; root:xnu-3248.60.10~1/RELEASE_X86_64 x86_64 /Users/shinsangho/freesurfer_subjects/NOR82_PJI \n mri_convert /Users/shinsangho/DTI_analysis/nor82_pji_t1/coT1.nii /Users/shinsangho/freesurfer_subjects/NOR82_PJI/mri/orig/001.mgz \n mri_convert.bin /Users/shinsangho/DTI_analysis/nor82_pji_t1/coT1.nii /Users/shinsangho/freesurfer_subjects/NOR82_PJI/mri/orig/001.mgz $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from /Users/shinsangho/DTI_analysis/nor82_pji_t1/coT1.nii... TR=1670.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (0.000121244, -1, 0) j_ras = (-0.0235518, -2.85817e-06, 0.999723) k_ras = (0.999723, 0.000121211, 0.0235518) writing to /Users/shinsangho/freesurfer_subjects/NOR82_PJI/mri/orig/001.mgz... /Users/shinsangho/freesurfer_subjects/NOR82_PJI/label #-------------------------------------------- #@# BA_exvivo Labels lh Fri Oct 4 17:43:23 BST 2019 \n mri_label2label --srcsubject fsaverage --srclabel /Users/shinsangho/freesurfer_subjects/fsaverage/label/lh.BA1_exvivo.label --trgsubject NOR82_PJI --trglabel ./lh.BA1_exvivo.label --hemi lh --regmethod surface \n srclabel = /Users/shinsangho/freesurfer_subjects/fsaverage/label/lh.BA1_exvivo.label srcsubject = fsaverage trgsubject = NOR82_PJI trglabel = ./lh.BA1_exvivo.label regmethod = surface srchemi = lh trghemi = lh trgsurface = white srcsurfreg = sphere.reg trgsurfreg = sphere.reg usehash = 1 Use ProjAbs = 0, 0 Use ProjFrac = 0, 0 DoPaint 0 SUBJECTS_DIR /Users/shinsangho/freesurfer_subjects FREESURFER_HOME /Applications/freesurfer Loading source label. Found 4129 points in source label. MRISread(/Users/shinsangho/freesurfer_subjects/NOR82_PJI/surf/lh.white): could not open file Starting surface-based mapping Reading source registration /Users/shinsangho/freesurfer_subjects/fsaverage/surf/lh.sphere.reg Rescaling ... original radius = 100 Reading target surface * /Users/shinsangho/freesurfer_subjects/NOR82_PJI/surf/lh.white* *No such file or directory* *ERROR: could not read /Users/shinsangho/freesurfer_subjects/NOR82_PJI/surf/lh.white* Darwin sinsanghoui-MBP 15.6.0 Darwin Kernel Version 15.6.0: Thu Jun 23 18:25:34 PDT 2016; root:xnu-3248.60.10~1/RELEASE_X86_64 x86_64 recon-all -s NOR82_PJI exited with ERRORS at Fri Oct 4 17:43:25 BST 2019 For more details, see the log file /Users/shinsangho/freesurfer_subjects/NOR82_PJI/scripts/recon-all.log To report a problem, see http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting ================================================== Best wishes, Sangho ᐧ

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