Dear Andrew,
sorry for the late reply.
Aren't there any error outputs for the two cases?
If not, would you mind uploading the subjects so I can take a look?
Cheers,
Eugenio
Juan Eugenio Iglesias
Postdoctoral researcher BCBL
www.jeiglesias.com
www.bcbl.eu
Legal disclaimer/Aviso legal/Lege-oharra: www.bcbl.eu/legal-disclaimer
From: "Andrew Schoen" <schoen.andr...@gmail.com>
To: "Freesurfer support list" <freesurfer@nmr.mgh.harvard.edu>
Sent: Wednesday, December 23, 2015 4:05:00 PM
Subject: [Freesurfer] Hippocampal Subfields (6.0) Error
Hi all,
We are running some hippocampal subfield segmentations for two independent
studies. They have already been processed through the standard pipeline (5.3),
so I was just running the following command:
recon-all -s ${subjectid} -hippocampal-subfields-T1
For both test cases, the processing seems to have halted (no more updates to
the log file), but the command keeps running. For one study, it trailed off
here:
************************************************************************************************************************
Resolution level 1 iteration 2 deformation iterations 13
Number of Meshes: 1
Using CG optimizer
Did one deformation step of max. 0.00037944 voxels in 14.6033 seconds
minLogLikelihoodTimesPrior =
2.3442e+06
Resolution level 1 iteration 2 deformation iterations 14
Number of Meshes: 1
Using CG optimizer
Did one deformation step of max. 1.3541e-06 voxels in 3.5131 seconds
minLogLikelihoodTimesPrior =
2.3442e+06
Resolution level 1 iteration 2 deformation iterations 15
Number of Meshes: 1
Using CG optimizer
Did one deformation step of max. 0 voxels in 30.0807 seconds
minLogLikelihoodTimesPrior =
2.3442e+06
maximalDeformation is too small; stopping
Iteration 3 of 7
(eof)
************************************************************************************************************************
and the other here:
************************************************************************************************************************
Making Left-Accumbens-area map to reduced label 13
--------------
Making Unknown map to reduced label 14
Computing hyperparameters for estimation of Gaussians parameters
Estimating typical intensities of molecular layer and alveus
For ML in T1, we assume gray with high N
In T2, we actually assume the same hypermean
Smoothing mesh collection with kernel size 1.500000 ...Smoothing class: 0
Smoothing class: 1
Smoothing class: 2
Smoothing class: 3
Smoothing class: 4
Smoothing class: 5
Smoothing class: 6
Smoothing class: 7
Smoothing class: 8
Smoothing class: 9
Smoothing class: 10
Smoothing class: 11
Smoothing class: 12
Smoothing class: 13
done
numberOfImages = 2
Image: 0
Image: 2
Iteration 1 of 7
(eof)
************************************************************************************************************************
Interestingly, for one study, we have T2-weighted images, and when I ran with
that (same subject as second log, above), it ran to completion fine.
Any idea what might be happening? Let me know if any other info would be
useful!
Thanks!
Andrew Schoen
Center for Healthy Minds
Waisman Center
University of Wisconsin - Madison
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