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Dear FreeSurfers, I am trying to run the longitudinal process including (recon-all -base and -long) for 5 different timepoints. But in my original data one the of five differs in the acquisition orientation and in the size of the field of view, so the results and especially the statistic is distorted. Four of my data sets have RPI as acquisition Parameter and a FOV of 230, the last data set has LPI and a FOV of 257. Does it even make sense to include this last dataset – is it even possible (due to different Parameters)? Do I have to pre-process this different data set?
Thank you in advance! Sam
Hi Samir,
you can first conform all inputs to 1mm isotropic using mri_convert --conform input output
It may make sense to add a covariate in the statistics for the different acquisition to control for a linear effect.
Best, Martin
On 25. May 2018, at 08:29, Samir Rekic rekic.samir08@hotmail.com wrote:
Dear FreeSurfers, I am trying to run the longitudinal process including (recon-all -base and -long) for 5 different timepoints. But in my original data one the of five differs in the acquisition orientation and in the size of the field of view, so the results and especially the statistic is distorted. Four of my data sets have RPI as acquisition Parameter and a FOV of 230, the last data set has LPI and a FOV of 257. Does it even make sense to include this last dataset – is it even possible (due to different Parameters)? Do I have to pre-process this different data set?
Thank you in advance! Sam _______________________________________________ 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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Martin Reuter -
Samir Rekic