Alternatively, you can run mris_preproc for both time point 1 and 2 to create separate files with all your subjects in them, then use mris_calc like below to create a difference file, then follow the standard command-line stream as is described on the wiki.
doug
Martin Reuter wrote:
Hi Sandra, (and the list, I think this might be interesting for others)
the longitudinal ?h.thickness files are in registration (within subject) so in order to compute the difference or the rate you can simply use: mris_calc -o lh.outdiff sdir2/surf/lh.thickness sdir1/surf/lh.thickness and for the rate, you can divide by time 1 thickness or by the average thickness. If the time points are not equally spaced across subjects, you can also divide by difference in time. It is best to smooth the thickness files before you do all this (i.e. within time point smooth the ?h.thickness files with mri_surf2surf).
then map everything to your template (e.g. fsaverage) with mri_surf2surf
- there you can stack the thick-differences or thick-rates with
mri_concat
- do the glm
Beste Gruesse, Martin
On Tue, 2010-06-29 at 21:50 +0200, Sandra Duezel wrote:
Hi Martin
I just have got your answer to the longitudinal processing question from Michele and have some other questions regarding the output data from the longitudinal stream. Our study contains MRI scans of 45 elderly subjects from 2 timepoints. I have done all steps from the longitudinal stream and it worked without any problems.
Now I would like calculate the thickness difference maps between the prae and post scans, which are already longitudinally processed.
I have tried the thickdiffmap-script using the <tp1>.long and <tp2>.long data. It creates a .mgz file in each subject but also a new folder "groupstudy" with the prae/post data resampled to fsaverage (its an .mgh file)
Is this the right way to calculate the difference for longitudinal data?
Do I also need to proceed with GLM analysis as suggestet in http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis or do I need to handle the longitudial data in a different way?
Thank you very much for your help and answers!
Best regards
Sandra
Am 29.06.2010 um 17:24 schrieb Martin Reuter:
There is a step by step description on the longitudinal stream. It basically means:
- to process your two time points individually through freesurfer
(standard processing). 2. to create a template for each subjects from these processed time points 3. to run the two time points again (passing it the template) to compute better longitudinal results (less variability, more accuracy).
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer