I am new here so first of all: thanks a lot for all the other interesting topics!
I didn't find my answer elsewhere so let me try here:
I am working on a medical project based on CT images comparison. One aim of our project is to show that several structures (bone, cartilage, etc...) suffer no objective measurement differences (size, shape and thickness mostly) between an old and a new technique.
So every sample was imaged twice (old vs new) and there are virtually no or few differences in our visual experience - but we have to prove it.
One way often used in the litterature is segmentation (Mimics or Mevis or another) then comparison of segmented objects.
I am currently having my structures of interest as point cloud files (derived from 3d segmentation).
They are mostly plane or plane-like so not very complicated. They have an actual scale in millimeters so no need to resize (which is a good starting point).
Cloud to cloud comparison was interesting and successful, but not really clinically relevant.
So I am looking for a way to compare thickness of two datasets between all the surface points / areas (so basically obtain the same kind of results as cloud to cloud but giving me the difference of thickness instead of distance between points)
I think maybe a Mesh approach would be suitable, but I may be wrong and am not familiar with these.
If you have any idea...
Thank you very much!