Has anyone come up with a systematic way of adjusting the NiftyReg parameters in BrainReg to get a more precise registration? I am currently repeating registration on the same file after changing a single parameter to compare outputs, but I’m sure there is a better way to go about optimizing the values.
I have read the descriptions of the parameters at Registration parameters - brainglobe. My impression is that while the descriptions are great information regarding what the parameters control, it is still unclear to me how adjusting a parameter up or down will affect the registration.
To better understand, I reviewed the NiftyReg documentation, the aMap article, and the Modat et al. paper on the deformation algorithms used. A lot of the information I encountered was beyond what I can understand in the time I have to devote to this which is unfortunate because I think to be able to confidently adjust the parameter values one would really need to understand what is in these articles. From the Methods section of the aMap article I see that “a parameter search was performed” and many of these values seem to be the defaults used with BrainReg registration; however, with my dataset the defaults are pretty far off.
I am happy to help develop a systematic approach if none exists. I am also happy to share my results and data to help any way I can.