12 research outputs found
Associations between aerobic fitness and brain structure in schizophrenia with a focus on hippocampal formation subfield volume [Abstract]
Bayesian Point Set Registration
Point set registration involves identifying a smooth invertible
transformation between corresponding points in two point sets, one of which may
be smaller than the other and possibly corrupted by observation noise. This
problem is traditionally decomposed into two separate optimization problems:
(i) assignment or correspondence, and (ii) identification of the optimal
transformation between the ordered point sets. In this work, we propose an
approach solving both problems simultaneously. In particular, a coherent
Bayesian formulation of the problem results in a marginal posterior
distribution on the transformation, which is explored within a Markov chain
Monte Carlo scheme. Motivated by Atomic Probe Tomography (APT), in the context
of structure inference for high entropy alloys (HEA), we focus on the
registration of noisy sparse observations of rigid transformations of a known
reference configuration.Lastly, we test our method on synthetic data sets.Comment: 15 pages, 20 figure