I’d like to have some estimation of how much of an outlier each of my landmarks is as I’m working through a 3D CLEM alignment. When I’m doing tilt series alignment for tomography, IMOD (eTomo) gives me a residual error value for the image of a fiducial that I’m tracking through the projections. I then have to correct the large residuals - usually the landmark is not aligned with the fiducial, so you have to move it to make them line up. As you do that, your mean residual error drops. This way, you have values to indicate how good your alignment is (although you have to be careful to not read too much into this).
So, I’m guessing that a Similarity or Affine BigWarp transform would make the LM and EM landmarks align with each other in 3D space less well than a Thin Plate Spline. Would there be a way to put a value on this difference and indicate it in the landmarks table? It would be a sort of equivalent to showing on the image how much distortion is needed to make the datasets fit each other. But with values, you could identify the landmarks that are creating a lot of distortion and try to fix them. Doing a manual FIB SEM CLEM alignment is quite an iterative process, and I’m really making it up as I go along. It would be nice to have a way to guide you through the process with some kind of metric for how good your alignment is.