Hi Laurel and Johannes, Pediatric: if the time distance is small it should also work in paediatric images. You can just test it on a couple cases and if too many edits would be required, then simply use the cross sectional processed results.
There is no thorough analysis, but missingness is not a big problem if you use Linear Mixed Effects Modeling. You can even include subjects with a single time point (but make sure you run it also through the longitudinal stream so that that single image undergoes the same processing steps as the rest). Best, Martin > On 9. Jul 2018, at 15:50, Mohn, Johannes <m...@mpib-berlin.mpg.de> wrote: > > > Dear FS Experts and Community, > > we are working on a longitudinal dataset of structural T1w images in a > pediatric sample assessed at 2 waves, 2 years apart (aged 6/7 and 8/9). > As far as we know, it is yet unresolved whether the Freesurfer longitudinal > pipeline is robust in pediatric samples, where the head size is still > changing or have there been any recent developments? > Also, is there any documentation on how missingness affects this Pipeline? > > We look forward to your response > > Thank you, > > Laurel and Johannes > > Jacobs Entwicklungsstudie > > Max-Planck-Institut für Bildungsforschung > Max Planck Institute for Human Development > Lentzeallee 94 > 14195 Berlin > > Tel.: 030-824 06 371 > E-Mail: jacobs-stu...@mpib-berlin.mpg.de > <mailto:jacobs-stu...@mpib-berlin.mpg.de> > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > <https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>
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