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We present a new method for cell segmentation which combines a marked point process model with a combinatorics-based method of finding global optima. The method employs an energy term that assesses possible segmentations by their fidelity to both local image information and a simple model of cell interaction, and we use a randomized iterative reweighting technique for its minimization. Our approach...
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...
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