GPU-Based Image Geodesics for Optical Coherence Tomography
Within a manifold framework, the interpolation of tomographic image time series is investigated. To this end, the metamorphosis model of a manifold of images is taken into account. 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 graphics hardware and a proper combination of GPU and CPU computation. First results for time series of optical coherence tomography images of a macular degeneration demonstrate the applicability of this geometric concept.
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