GPU Based Geodesics of Image Time SeriesMS28

We investigate the interpolation of image time series using the metamorphosis model of a manifold of images. Based on a variational time discretization, discrete geodesic paths in this space of images are computed. The space discretization is based on finite elements spanned by tensor product cubic B-splines. An efficient implementation is obtained by utilizing a proper combination of GPU and CPU computation. Numerical results of the approach on optical coherence tomography image series are shown.

This presentation is part of Minisymposium “MS28 - Diffeomorphic Image Registration: Numerics, Applications, and Theory (2 parts)
organized by: Andreas Mang (Department of Mathematics, University of Houston) , George Biros (Institute for Computational Engineering and Sciences, University of Texas at Austin) .

Benjamin Berkels (RWTH Aachen University)
Michael Buchner (Institute for Numerical Simulation, University of Bonn)
Alexander Effland (Universität Bonn)
Martin Rumpf (University of Bonn)
computer vision, image registration, inverse problems, nonlinear optimization