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Robust and accurate segmentation of blood vessels is important for treatment and diagnosis of cardiovascular diseases. Here, we introduce a new approach for 3D segmentation of vessels which is formulated as a convex parameter estimation problem and combined with an incremental tracking approach. Parameter values are determined as global optimum of a semidefinite program and admissible shape variations...
A variational approach is presented to the estimation of turbulent fluid flow from particle image sequences in experimental fluid mechanics. The approach comprises two coupled optimizations for adapting size and shape of a Gaussian correlation window at each location and for estimating the flow, respectively. The method copes with a wide range of particle densities and image noise levels without any...
This paper studies automatic segmentation of multiple motions from tracked feature points through spectral embedding and clustering of linear subspaces. We show that the dimension of the ambient space is crucial for separability, and that low dimensions chosen in prior work are not optimal. We suggest lower and upper bounds together with a data-driven procedure for choosing the optimal ambient dimension...
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