Dear all,
I would like to apply the SPM12 serial longitudinal processing pipeline on a data set including four time points per person scanned over a period of three weeks where a treatment was applied. I understand the longitudinal toolbox was originally designed to identify subtle volumetric changes over years, therefore I am looking for ways to adapt the serial pipeline to my paradigm if appropriate.
As previously suggested on the mailinglist, I run the following preprocessing steps:
1) Run SPM12 serial registration to generate the subject average and Jacobian maps for each of the four time points. In previous posts it has been suggested to use fractions of a year to specify the times between scans if data is collected in less than a year. My data has been collected over a period of a few weeks, which results in very small numbers for specified time differences between scans.
2) Segment average for each subject, generating c1, rc1, rc2
3) Multiply c1*jd per subject for each time point
4) Run DARTEL to create template, aligning rc1 and rc2 images for all subjects
5) Normalize to MNI space and smooth, using all four c1*jd images and flowfield for each subject
I would be grateful if you could advise me on two questions:
Is this procedure valid?
Is there a way to handle the time difference issue in the serial registration for the short time period used in this study?
Your help is greatly appreciated.
Best regards
Isabel Ellerbrock
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