Hi, I saw a lot of tutorials asking us to do ACPC alignment before doing FreeSurfer recon-all.
But they didn’t say why in detail.
ACPC alignment would center the MRI at the AC’s location, through the PC.
So I wonder anyone knows why would we do that before recon-all,
and what would happen if we don’t?
Also, where does the original MRI centered in DICOM?
I’ve loaded a .nii file converted from DICOM like below, and the origin seems random.
This step will move the image in a way that effectively “centers” the image. Specifically, the image will be moved so that a horizontal line drawn from the front to the back of the brain will pass through both landmarks, and a horizontal line drawn from the temporal lobes and a vertical line from the top of the brain to the bottom bisect at the midpoint of the two landmarks.
I believe that ACPC alignment could prevent Talairach registration
errors/inaccuracies in recon-all which could have profound effect on subsequent
skullstrip and subcortical labeling (it could at least prevent to disastrous
errors which some other users reported recently, such as this: http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg51789.html). This
could also help to mutual registration of data of multiple sessions (i.e. in
longitudinal studies) to compensate different head positioning.
There is not a standard centering, which is why ACPC alignment can be helpful.
Also, I found that like FreeSurfer, when doing parcellation, the software would register the T1 to fsaverage, pre-aligned AC-PC seems would simplify this process. Please correct me if I’m incorrect.
For completeness, the starting origin is not random. For DICOM MRI’s, the origin of the image is the isocenter for the magnet (for CT scans it is the table center). This is preserved when you convert a DICOM image to NIfTI. This origin is a good starting estimate for co-registering different series within a session: e.g. adjusting for spatial distortions inherent between T1 and T2* (fMRI) modalities.
This origin is less useful when we normalize an individual’s scan to a population based template. Here it makes sense to adjust the origin to the anatomical origin of the template: the anterior commissure. This gives a good starting estimate for the normalization, and avoids the likelihood of the algorithm being trapped in a local minima.