  Recent advances in imaging technology now provide us with 3D images of
developing organs. These can be used to extract 3D geometries for simulations
of organ development. To solve models on growing domains, the displacement
fields between consecutive image frames need to be determined. Here we develop
and evaluate different landmark-free algorithms for the determination of such
displacement fields from image data. In particular, we examine minimal
distance, normal distance, diffusion-based and uniform mapping algorithms and
test these algorithms with both synthetic and real data in 2D and 3D. We
conclude that in most cases the normal distance algorithm is the method of
choice and wherever it fails, diffusion-based mapping provides a good
alternative.
