mris_preproc --target 0_1 --s avg_subject_91_noexpopts --hemi lh --meas thickness --out avg_91_to_lh.mgh

where 0_1 is target patient to map thickness, from avg_subject_91_noexpopts, optained from make_average_subject.

От: freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> от имени Douglas N. Greve <dgreve@mgh.harvard.edu>
Отправлено: 3 февраля 2020 г. 20:51
Кому: freesurfer@nmr.mgh.harvard.edu
Тема: Re: [Freesurfer] Thickness group normalization

Do you have a group of subjects that you want to use as an average? If so, you can just map all their thickness maps to your patient subject with
mris_preproc --target patientsubjectname [then usual arguments]
Compute the mean with
mri_concat outputofmris_preproc.mgz --mean --o groupmean.mgz
You can then compare groupmean.mgz to your patient on a vertex-by-vertex baiss

On 2/3/2020 12:16 PM, Vyacheslav Yarkin wrote:

External Email - Use Caution

Hello Freesurfer Team,

Would you be so kind to provide freesurfer steps to implement warping fsaverage mean thickness data on individual subject inflated brains ?

I am using expert opts to disable cortical thickness restriction, and set mris_thickness -max 20 as I want to find fcd to cortical surfaces. The reason i need normalization is that there is zones like sulci orbitales have bigger thickness accross subjects group ( control ) and have red LUTs on inflated thickness map. So i would like to normalize thickness over control group, to use it on patients to exclude "normal" thickness excedings to include only increased FCD zones. The main issue I faced is how to warp fsaverage mean thickness data on individual subject's inflated brain as they have vertices number missmatch.

Steps I tried:

1) make_average_subject

2) mri_concat --mean to create mean thicknesses over group

Thank you
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer