Hi Emily,

The log file you sent shows nuclei of the amygdala, which were not present in 6.0. Version must be being mixed somewhere… Can you please double check?

Cheers,

/Eugenio

Juan Eugenio Iglesias

Senior research fellow

CMIC (UCL), MGH (HMS) and CSAIL (MIT)

http://www.jeiglesias.com

From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Emily K Clarke <ekc23@duke.edu>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Wednesday, October 7, 2020 at 14:56
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Hippocampal subfields error

External Email - Use Caution

Hi Eugenio,

No, I don't think so - we're running recon-all and using the hippocampal pipeline from FS 6.0. I bug tested with the FS 6.0dev version and found that that hippocampal pipeline worked okay, but since we're combining data with an older dataset we need to be able to extract the older hippocampal subfields, starting with the recon-all hippocampal subfields processing.

Thanks,

Emily

Date: Wed, 9 Sep 2020 21:21:41 +0000

From: "Iglesias Gonzalez, Juan E." <JIGLESIASGONZALEZ@mgh.harvard.edu>

Subject: Re: [Freesurfer] Hippocampal subfields error

To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>

Message-ID: <25DF95C0-873A-4906-9D51-A94CF022375D@mgh.harvard.edu>

Content-Type: text/plain; charset="utf-8"

Hi Emily.

Is it possibly that you may be mixing FS versions, by any chance?

Cheers,

/Eugenio

Juan Eugenio Iglesias

Senior research fellow

CMIC (UCL), MGH (HMS) and CSAIL (MIT)

https://urldefense.com/v3/__http://www.jeiglesias.com__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsAg3rWMo$

From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Emily K Clarke <ekc23@duke.edu>

Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>

Date: Wednesday, September 9, 2020 at 15:53

To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>

Subject: [Freesurfer] Hippocampal subfields error

External Email - Use Caution

Hi Eugenio,

We?re still running into the issue where running recon-all with the hippocampal subfields tag isn?t actually generating any of the hippocampal files. I?ve included our full recon-all log below. We already examined the scans, and they look perfectly normal ? do you know why this might be happening?

Thanks,

Emily Clarke-Rubright

Morey Neuroimaging Lab

The whole log message:

#--------------------------------------------

#@# Hippocampal Subfields processing (T1 only) left Mon Aug 10 18:54:21 EDT

2020

------------------------------------------

Setting up environment variables

---

LD_LIBRARY_PATH is

.:/usr/local/packages/freesurfer_v6.0.0/MCRv80/runtime/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/bin/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/os/glnxa64:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/native_threads:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/server:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64/client:/usr/local/packages/freesurfer_v6.0.0/MCRv80/sys/java/jre/glnxa64/jre/lib/amd64:/usr/lib64/qt5/plugins/platforms:/usr/local/packages/ants-2.3.4/lib:/usr/lib64/openmpi/lib:

Warning: application is running on a locale different from the original

platform locale.

Warning: No display specified. You will not be able to display graphics on

the screen.

Registering imageDump.mgz to hippocampal mask from ASEG

This file does not contain MRI parameters

$Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $

--mov: Using imageDump.mgz as movable/source volume.

--dst: Using /mnt/BIAC/.users/ch186/

duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz

as target volume.

--lta: Output transform as trash.lta .

--mapmovhdr: Will save header adjusted movable as

imageDump_coregistered.mgz !

--sat: Using saturation 50 in M-estimator!

reading source 'imageDump.mgz'...

reading target '/mnt/BIAC/.users/ch186/

duhsnas-pri.dhe.duke.edu/dusom_morey/Data/Lab/PGC/T1s/Duke_data/Freesurfer/addl/cch/12588326/tmp/hippoSF_T1_v10_left//hippoAmygBinaryMask_autoCropped.mgz'.

Registration::setSourceAndTarget(MRI s, MRI t, keeptype = TRUE )

Type Source : 0 Type Target : 3 ensure both FLOAT (3)

Reordering axes in mov to better fit dst... ( -1 3 -2 )

MRIreorder() -----------

xdim=-1 ydim=3 zdim=-2

src 131 241 99, 0.250000 0.250000 0.250000

dst 131 99 241, 0.250000 0.250000 0.250000

Determinant after swap : 0.015625

Mov: (0.25, 0.25, 0.25)mm and dim (131, 99, 241)

Dst: (1, 1, 1)mm and dim (38, 40, 59)

Asserting both images: 1mm isotropic

- reslicing Mov ...

-- changing data type from 0 to 3 (noscale = 0)...

-- Original : (0.25, 0.25, 0.25)mm and (131, 99, 241) voxels.

-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.

-- Reslicing using cubic bspline

MRItoBSpline degree 3

- reslicing Dst ...

-- Original : (1, 1, 1)mm and (38, 40, 59) voxels.

-- Resampled: (1, 1, 1)mm and (38, 40, 61) voxels.

-- Reslicing using cubic bspline

MRItoBSpline degree 3

Registration::computeMultiresRegistration

- computing centroids

- computing initial transform

-- using translation info

- Get Gaussian Pyramid Limits ( min size: 16 max size: -1 )

- Build Gaussian Pyramid ( Limits min steps: 0 max steps: 1 )

- 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.

https://urldefense.com/v3/__http://dx.doi.org/10.1016/j.neuroimage.2010.07.020__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsb0h_GYU$

https://urldefense.com/v3/__http://reuter.mit.edu/papers/reuter-robreg10.pdf__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsE_-J7bg$

$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 )

- 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.

https://urldefense.com/v3/__http://dx.doi.org/10.1016/j.neuroimage.2010.07.020__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsb0h_GYU$

https://urldefense.com/v3/__http://reuter.mit.edu/papers/reuter-robreg10.pdf__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsE_-J7bg$

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

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

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 )

- 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.

https://urldefense.com/v3/__http://dx.doi.org/10.1016/j.neuroimage.2010.07.020__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsb0h_GYU$

https://urldefense.com/v3/__http://reuter.mit.edu/papers/reuter-robreg10.pdf__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsE_-J7bg$

$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 )

- 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.

https://urldefense.com/v3/__http://dx.doi.org/10.1016/j.neuroimage.2010.07.020__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsb0h_GYU$

https://urldefense.com/v3/__http://reuter.mit.edu/papers/reuter-robreg10.pdf__;!!OToaGQ!54kYqoLJMazG-e4wE3yKpehQ-BMMjAGSsGWeQv_zzG6tzdVr_8s9dgvsE_-J7bg$

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

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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End of Freesurfer Digest, Vol 199, Issue 17

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