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Dear FreeSurfer experts,
I want to get with mris_anatomical_stats the stats from the four lobes,
Frontal, Parietal, Temporal and Occipital as suggest here (
https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation), but
without the cingulate.
I
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--
*From:* Amir Shmuel, Dr.
*Sent:* 03 August 2018 15:55
*Subject:* Resting-State and Brain Connectivity 2018: abstract submission
remains open until August 11
*Resting-State and Brain Connectivity 2018: abstract submission
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Dear FS experts,
This paper was published in 2013:
https://www.sciencedirect.com/science/article/pii/S1053811913007064?via%3Dihub#s0040
I was just wondering if the current version of FreeSurfer can still
introduce bias in cortical volume measures if I
I don't think it is correct conceptually. By including SNR as a
covariate, you are saying that you expect the thickness to increase with
higher SNR and decrease with lower SNR. This does not make sense to me.
It sounds like you are trying to do a mixed effects analysis where you
weight by the
To add on, the origin is changed in that the "first voxel" is not the
same in the 256^3 volume as it is in the original dicom. Having said
that, all our files (eg, mgz and nifti) have a matrix that converts a
col, row, slice into the scanner RAS, so you can always find your way
back to the dic
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Daer FS experts,
I would like to inquire about including SNR as a covariate for the between
groups cpmparison in cortical thickness. Is this procedure correct
mathematically? Do I need to demean the SNA values before including it
covariates? Finally,
Hi Ritesh
Doug can correct any inaccuracies, but
1. Yes, unless you tell recon-all not to.
2. I'm not sure what you mean by the origin, but we do keep track of
the ras coordinates of the center of the volume after resampling (the so-called
"cras").
3. We do keep track of the original dicom
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Dear Vasudev,
It is expected that you get different volume estimates with different atlases
(FreeSurfer vs CobraLab), as the manual delineation protocols that were used to
create them are very different (e.g., see Yushkevich et al., NeuroImage, 2015).