Whole cell tracking through the optimal control of geometric evolution laws
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Cell tracking algorithms which automate and systematise the analysis of time lapse image data sets of cells are an indispensable tool in the modelling and understanding of cellular phenomena. In this study we present a theoretical framework and an algorithm for whole cell tracking. Within this work we consider that "tracking" is equivalent to a dynamic reconstruction of the whole cell data (morphologies) from static image data sets. The novelty of our work is that the tracking algorithm is driven by a model for the motion of the cell. This model may be regarded as a simplification of a recently developed physically meaningful model for cell motility. The resulting problem is the optimal control of a geometric evolution law and we discuss the formulation and numerical approximation of the optimal control problem. The overall goal of this work is to design a framework for cell tracking within which the recovered data reflects the physics of the forward model. A number of numerical simulations are presented that illustrate the applicability of our approach.
Blazakis , K N , Madzvamuse , A , Reyes-Aldasoro , C C , Styles , V & Venkataraman , C 2015 , ' Whole cell tracking through the optimal control of geometric evolution laws ' , Journal of Computational Physics , vol. 297 , pp. 495-514 . https://doi.org/10.1016/j.jcp.2015.05.014
Journal of Computational Physics
(C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
DescriptionThis work (A.M., V.S. and C.V.) is supported by the Engineering and Physical Sciences Research Council, UK grant (EP/J016780/1) and the Leverhulme Trust Research Project Grant (RPG-2014-149). K.B. was partially supported by the Embirikion Foundation Grant (2011-2014) – Greece.
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