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Hi again, Andrew.
If you run recon-all-clinical and then create the base, it won’t work because:
Hopefully we’ll have a longitudinal version of recon-all-clinical at some point!
Cheers,
/E
--
Juan Eugenio Iglesias
http://www.jeiglesias.com
From:
freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Andrew Dedinas Geoly <ageoly@stanford.edu>
Date: Wednesday, May 31, 2023 at 15:40
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] recon-all-clinical Longitudinal workflow
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Thank you for your quick response!
>From my understanding of the longitudinal processing stream, the individual recon-all (cross) outputs from each time point are used to create a base model that averages the cross outputs. Finally,
recon-all long is used for each of those cross outputs and the information from the within-subject base template.
My thought was that I could use reconall_clinical simply to create the (cross) outputs from the first step and then those would be used for step 2 and 3.
Would this be a feasible approach?
Best,
Andrew
From: freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Iglesias Gonzalez, Juan E. <JIGLESIASGONZALEZ@mgh.harvard.edu>
Sent: Saturday, May 27, 2023 8:41 AM
To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] recon-all-clinical Longitudinal workflow
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Dear Andrew,
These are both great questions!
Sorry for not having better tools at the moment, but we are in a transitional period in which we are releasing machine learning tools that only replace parts of the main stream and some functionalities are
not fully supported yet.
Cheers,
/Eugenio
--
Juan Eugenio Iglesias
http://www.jeiglesias.com
From:
freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Andrew Dedinas Geoly <ageoly@stanford.edu>
Date: Friday, May 26, 2023 at 23:38
To: freesurfer@nmr.mgh.harvard.edu <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] recon-all-clinical Longitudinal workflow
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