Re: [Freesurfer] Longitudinal Hippocampal Subfields - error during segmentation {Disarmed}

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Any guidance on this error is appreciated. I am still receiving the same output stated earlier.

Rachel Phillips

________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Rachel Phillips rachel.phillips@duke.edu Sent: Monday, January 7, 2019 9:11:47 AM To: Freesurfer support list Subject: Re: [Freesurfer] Longitudinal Hippocampal Subfields - error during segmentation {Disarmed}

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Version 6.0

Thanks,

Rachel

________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Iglesias Gonzalez, Eugenio e.iglesias@ucl.ac.uk Sent: Monday, January 7, 2019 2:50:57 AM To: freesurfer@nmr.mgh.harvard.edu; Freesurfer support list Cc: Courtney Haswell Subject: Re: [Freesurfer] Longitudinal Hippocampal Subfields - error during segmentation {Disarmed}

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Hi Rachel This is very weird. What exact version are you using? 6.0 or dev? Cheers Eugenio

Juan Eugenio Iglesias

ERC Senior Research Fellow Centre for Medical Image Computing (CMIC) University College London

Research staff Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School

Research Affiliate Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology

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________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Rachel Phillips rachel.phillips@duke.edu Sent: Friday, January 4, 2019 7:43:45 PM To: freesurfer@nmr.mgh.harvard.edu Cc: Courtney Haswell Subject: [Freesurfer] Longitudinal Hippocampal Subfields - error during segmentation

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Hello,

I have run a longitudinal sample (up to 4 timepoints per subject) through the Freesurfer 6.0 longitudinal processing pipeline, and currently I am attempting to produce the longitudinal hippocampal subfield segmentation with the following command: longHippoSubfieldsT1.sh <baseID> [SubjectsDirectory]. I am receiving the following error: "Error using SegmentSubfeldsT1Longitudinal (line 441) The vector of prior probabilities in the mesh nodes must always sum to one over all classes".

Below is an example of the output that precedes this error:

[> In SegmentSubfieldsT1Longitudinal at 418] 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 SegmentSubfieldsT1Longitudinal (line 441) The vector of prior probabilities in the mesh nodes must always sum to one over all classes

Any guidance on this error would be greatly appreciated.

Thanks, Rachel