External Email - Use Caution
Hello Freesurfer experts!
I am conducting a longitudinal GMV and CT analysis of mTBI participants who received an experimental single-dose pharmacological treatment. We collected GE Bravo (0.9mm isotropic) T1w data pre, immediately after (~ 4 days after intervention) and 1-month following the intervention.
I have been working with the recon-all longitudinal pipeline stream (7.1.1) but have noticed pretty significant errors in terms of skull stripping and segmentation (participants are veterans with somewhat random lesion / atrophy patterns).
I have tested your new recon-all-clinical program (7.4.0) on some of my worst cases and it is performing remarkably well. I am doing some more digging into the various synth segmentation packages available in FS newest versions and was wondering what the best course of action would be for integrating recon-all-clinical or synthseg into a longitudinal workflow.
1.Could I use the recon-all-clinical outputs as the "cross" for later base and long template construction? 2. SynthSeg and SCLimbic seem to have very good test-retest reliability-- would it be feasible to use the independent segmentation extractions from those and bypass the longitudinal stream entirely (not saying I would want to but I am curious)?
Any and all help here would be greatly appreciated, and I thank you very much for your time.
Warmest regards, Andrew
---
Andrew D. Geoly, MS
Research Data Analyst 1
Brain Stimulation Lab
Department of Psychiatry and Behavioral Sciences
Stanford University School of Medicine
External Email - Use Caution
On 5/26/2023 5:39 PM, Andrew Dedinas Geoly wrote:
External Email - Use Caution
Hello Freesurfer experts!
I am conducting a longitudinal GMV and CT analysis of mTBI participants who received an experimental single-dose pharmacological treatment. We collected GE Bravo (0.9mm isotropic) T1w data pre, immediately after (~ 4 days after intervention) and 1-month following the intervention.
I have been working with the recon-all longitudinal pipeline stream (7.1.1) but have noticed pretty significant errors in terms of skull stripping and segmentation (participants are veterans with somewhat random lesion / atrophy patterns).
I have tested your new recon-all-clinical program (7.4.0) on some of my worst cases and it is performing remarkably well. I am doing some more digging into the various synth segmentation packages available in FS newest versions and was wondering what the best course of action would be for integrating recon-all-clinical or synthseg into a longitudinal workflow.
1.Could I use the recon-all-clinical outputs as the "cross" for later base and long template construction?
I don't know. Hopefully Eugenio/Karthik will weigh in
- SynthSeg and SCLimbic seem to have very good test-retest
reliability-- would it be feasible to use the independent segmentation extractions from those and bypass the longitudinal stream entirely (not saying I would want to but I am curious)?
sclimbic generates segs that are not in the long stream, so there is no long option. My experience with synthseg is that it is inferior to the long stream on long data
Any and all help here would be greatly appreciated, and I thank you very much for your time.
Warmest regards, Andrew
Andrew D. Geoly, MS
Research Data Analyst 1
Brain Stimulation Lab
Department of Psychiatry and Behavioral Sciences
Stanford University School of Medicine
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://secure-web.cisco.com/1MtioKA64TCULuiinjIH4QyWe2hiHaKCHzIns0CxttO-bay...
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Uuummm I don’t think this would work, as a lot of our intermediate files (eg norm.mgz) are not comparable to their counterparts in the standard recon-all stream. Sorry!
-- Juan Eugenio Iglesias http://secure-web.cisco.com/1R9UOepVdGkzRhS_JbSZ7bkBYP0OujnEdjEaN6GrFG8xXfSY...
From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Douglas N. Greve dgreve@mgh.harvard.edu Date: Tuesday, June 20, 2023 at 9:32 AM To: freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu, Iglesias Gonzalez, Eugenio e.iglesias@ucl.ac.uk, Gopinath, Karthik KGOPINATH@mgh.harvard.edu Subject: Re: [Freesurfer] recon-all-clinical
External Email - Use Caution
On 5/26/2023 5:39 PM, Andrew Dedinas Geoly wrote:
External Email - Use Caution Hello Freesurfer experts!
I am conducting a longitudinal GMV and CT analysis of mTBI participants who received an experimental single-dose pharmacological treatment. We collected GE Bravo (0.9mm isotropic) T1w data pre, immediately after (~ 4 days after intervention) and 1-month following the intervention.
I have been working with the recon-all longitudinal pipeline stream (7.1.1) but have noticed pretty significant errors in terms of skull stripping and segmentation (participants are veterans with somewhat random lesion / atrophy patterns).
I have tested your new recon-all-clinical program (7.4.0) on some of my worst cases and it is performing remarkably well. I am doing some more digging into the various synth segmentation packages available in FS newest versions and was wondering what the best course of action would be for integrating recon-all-clinical or synthseg into a longitudinal workflow.
1.Could I use the recon-all-clinical outputs as the "cross" for later base and long template construction? I don't know. Hopefully Eugenio/Karthik will weigh in
2. SynthSeg and SCLimbic seem to have very good test-retest reliability-- would it be feasible to use the independent segmentation extractions from those and bypass the longitudinal stream entirely (not saying I would want to but I am curious)? sclimbic generates segs that are not in the long stream, so there is no long option. My experience with synthseg is that it is inferior to the long stream on long data
Any and all help here would be greatly appreciated, and I thank you very much for your time.
Warmest regards, Andrew
---
Andrew D. Geoly, MS
Research Data Analyst 1
Brain Stimulation Lab
Department of Psychiatry and Behavioral Sciences
Stanford University School of Medicine
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Andrew Dedinas Geoly -
Douglas N. Greve -
Iglesias Gonzalez, Juan E.