If you have a registration LTA file (eg, from bbregister), the you can run something like
set gcam = $SUBJECTS_DIR/$subject/cvs/final_CVSmorph_tocvs_avg35_inMNI152.m3z set dstreg = $FREESURFER_HOME/subjects/cvs_avg35_inMNI152/mri.2mm/register.lta mri_vol2vol --gcam input.nii.gz reg $gcam $dstreg 0 0 output.nii.gz
On 8/5/2020 9:31 AM, Zollei, Lilla,Ph.D. wrote:
Hi Peter, Running the currently existing command, implicitly assumes that your fMRI data is in the same spatial coordinate space (with the same resolution) as the norm that you used for mri_cvs_register. You will need to use the --reg flag to input the fmri-2-structural transform. Best, Lilla
*From:* freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu on behalf of Peter Sperrer e1226992@student.tuwien.ac.at *Sent:* Wednesday, August 5, 2020 9:17 AM *To:* freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu *Subject:* [Freesurfer] mri_cvs_register for fMRI
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Dear FreeSurfer experts,
My goal is to morph fMRI (data in voxel space) for best possible intersubject GM-overlap. I am using /mri_cvs_register/ as it seemed like a perfect tool for this.
I have already run /recon-all /on the anatomical scan (160x239x200 voxels at 1x1x1mm) as well as /mri_cvs_register --mov [anatomical] --mni/.
The resulting normalized brain (/final_CVSmorphed_tocvs_avg35_inMNI152_norm.mgz/) looks pretty good, maybe except for a remaining piece of skull, which does not seem to have impaired the brain data, though.
Functional data has been ST-corrected, realigned and coregistered to the anatomical data in SPM.
Unfortunately, when I try to morph the fMRI images using
/mri_vol2vol --mov [PreprocessedFunctional.nii] --o [MorphedPreprocessedFunctional.nii] --m3z cvs/final_CVSmorph_tocvs_avg35_inMNI152.m3z --noDefM3zPath --targ cvs/final_CVSmorphed_tocvs_avg35_inMNI152_norm.mgz/
I end up with a strangely distorted, cropped and ill-oriented image. The file size and resolution is also enormous.
First of all, do you have any suggestions on what could have gone wrong? Is there a better way than using mri_cvs_register to normalize fMRI data so gyri and sulci between subjects match?
Since I do not need such high resolution for smoothing and analysis, is there a better way than just down-sampling after the morph?
Please excuse if any of these questions seem to have obvious answers to you, I am rather new to using FreeSurfer.
I have already searched the mailing list archive and did not find a solution to my problem but only a slightly related problem from 2013 (https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg30673.html)
In the solution it was also hinted that morphing fMRI data might be further supported in the future. Is there a tool or function which has been developed since then?
I appreciate your advice!
Thank you very much!
Kind regards
Peter Sperrer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer