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Tracking nano-metric particles in a biological environment is a very difficult task because of the low signal intensity and the high mobility of these small objects. The task becomes nearly impossible for classical tracking procedures when the targets are labeled with a marker that is not strictly specific, because in this case dynamic structures in the cell are also visible. To address this limitation,...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filtering, it relies on a constrained, medial-based geometric model and on an original sampling scheme for the selection of tracking hypotheses. A key property of this new sampling scheme is the ability to take into account a distribution...
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