I have a large set of clinical 2D T1 images that I would like to warp to a standard space for automated segmentation. Are there any AFNI tools that I can use for this?
If you look at the 3dQwarp help, you can search for “2D” to see more information about doing this.
You don’t give enough information to provide a better answer than Paul has given. Are these a single 2D image per subject? Or a collection of 2D images per subject, with very thick slices (say 5 mm thick, with 1 mm in plane resolution)?
These are 1 mm in plane resolution clinical T1 with whole brain coverage.
The difficulty with such volumes is that the through-slice resolution is typically 5 mm, which makes the in-slice images look good (very high SNR), but makes it hard to match them to a template dataset at 1 mm resolution. It is possible to resample them to a 1 mm grid in all 3 directions (“isotropic”), and then try the standard alignment tools. However, segmentation will be inaccurate since the resolution in the z direction will still be lousy.
If I were trying this, I would assemble the slices into a 3D dataset, then try the @SSwarper command to see how well it works. Probably a fair amount of swearing at the computer will be involved along the way.
If you need some help with this, you can upload some data, and I’ll try to take a look.