BAYESIAN REGISTRATION OF MODELS USING FEM EIGENMODES
Mike Syn and Richard Prager
September 1995
Highest Confidence First (HCF) estimation is applied to deterministic scaled-ordered non-rigid registration of organ models. A local Posterior energy measure is computed from Bayesian combination of local Prior and Likelihood energy measures, over a Markov Random Field (MRF) defined over the Finite Element neighbourhood of every element node. Prior energy is derived from the Gompertz metric of biological growth, and Likelihood energy is derived from the biologically meaningful similarity between local FEM eigenmode displacement components. The Centroid Size metric is generalised to give the characteristic scale of an organ model, which allows for normalisation of model size and eigenmode magnitude. Linear axes along which modal moments act are used as an estimate of intrinsic model pose, so that initial rigid-body registration can be achieved.
If you have difficulty viewing files that end '.gz',
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
web site.
If you have difficulty viewing files that are in PostScript, (ending
'.ps' or '.ps.gz'), then you may be able to
find tools to view them at
the gsview
web site.
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.