I have longitudinal data:

Three time-points [T1-T3] with an interval of about 6 months between T1 and T2 and 6 months between T2 and T3 from a control group as well as from a clinical group (again three time-points [T1-T3] with an interval of about 6 months between T1 and T2 and 6 months between T2 and T3).

- For control group: 48 (for T1), 36 (for T2) and 33 (for T3)

- For clinical group: 38 (for T1), 33 (for T2) and 31 (for T3)

I was wondering if it's fine to consider and combine three time-points within each group as independent samples for classification purposes (i.e.,  N = 117 (48+36+33) for the control group and N = 102 (38+33+31) for clinical group) between the two groups (based on brain morphometry measures). If so, I was wondering whether the recon-all should be done in the longitudinal way (MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing) i.e., making it unbiased towards a specific time-point, OR, the recon all should be run cross-sectionally so that we can keep all the time-points independent from each other.