Also, unless something is wrong with your processing or time point naming, you should get different volumes also for each time point in the longitudinal stream. Manually open the aseg.stats and check to determine if the problem is in way you processed the longitudinal data or when creating the stats.
It can be that volumes are consistently smaller or larger in long processing vs cross sectional processing, because there are extra processing steps that consistently change the way we compute these values. The longitudinal measures will be more reliable.
Best, Martin
On 05/09/2017 04:52 PM, Douglas Greve wrote:
Sorry, I'm not sure what you are trying to do. Can you send command lines?
On 5/9/17 6:42 AM, Ferdi van de Kamp wrote:
Hi all,
My question is twofold
using an user specified ROI in MNI512-space I ask Freesurfer to create tables for both cross-sectionally& longitudinally processed data.
Mri_segstats performed over both cross-sectional data folders and longitudinal data folders
However, when inspecting the data, the NVoxels for all time points in the longitudinal data are equal, while in the cross-sectional they differ (and are generally larger). Is this to be expected?
In addition to NVoxels and mean intensity, our lab would like to use other measures such as thickness, does anyone know the correct function to call for that information?
Right now the pipeline look like this:
Step1 standardised labels from volumes
This step is focused on the ROIs, not the subjects, is submitted as a single job
Uses /mri_vol2vol /and /mri_cor2label/.
Step 2 Create personalised labels, volumes & tables
This is the part that is submit to the cluster for each subject (separate for cross-sectional and longitudinal). It uses /mri_label2label/, /mri_label2vol /and /mri_segstats/.
Thanks!
Ferdi van de Kamp
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