It's possible that specifying a -master or -mast_dxyz may help... However - if you're planning to do things in group (standard) space, then I suspect you'd have the best luck downloading the SUMA surfaces for either TT_N27 or MNI and using those segmentations to do your ROI analysis.

There's some problem with using a standard affine warp for moving your segmentations up to group space. The most striking is that affine warps tend to favor global alignment over local structures (Kochunov et al., 2002 in NeuroImage) and the Freesurfer segmentations have a lot of local structures defined! So if you can do things with the group template segmentation, that may help. Otherwise, if you want to use the individual subject segmentations, I'd recommend you use the AFNI nonlinear warp (3dQwarp, add -tlrc_NL_warp to your proc.py command). Then you can use the 3dNwarpApply to move your segmentations to standard space while preserving both local and global properties.

-Peter