I know it has been mentioned in many posts that there are plans in the future to include cross-correlation and/or MI metrics to mrregister as they are not yet implemented. That being said, I was wondering how exactly the cross-correlation metric was implemented in Raffelt et al. 2011, Symmetric diffeomorphic registration of fibre orientation distributions in Neuroimage. Was this coded in-house? or was this analysis performed using ants software?
Following my post (Poor registration with mrregister compared with ANTs), which has considerably improved my original registration, I have pushed the registration for my patient population as far as I can go with the squared difference metric. However, as was noted, there are still some differences that can be improved.
Since ANTs CC worked better on my FA maps than the squared difference metric (see figure in previous post), I was curious to see if I could achieve a similar result on my fod volumes (and also to not mix metrics). I’m wondering if it is feasible to estimate transformations with ANTs (using FODs as input images, and the CC metric), and then mrtrix functions to reorient the fod’s after a single iteration (was this what was done in the paper, actually?). If so, it seems like something that is reasonably codable. In any case, I am very interested in using the same (or at least, an adapted) methodology as in Raffelt et al. 2011, even if it is ultimately longer than mrregister.
Thanks for any direction in this,