Whole cell tracking through the optimal control of geometric evolution laws
Whole cell tracking through the optimal control of geometric evolution laws
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DOI：
10.1016/j.jcp.2015.05.014
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发表时间：
2015-09-15
影响因子：
4.1
通讯作者：
Venkataraman, Chandrasekhar
中科院分区：
文献类型：
--
作者：
Blazakis, Konstantinos N.;Madzvamuse, Anotida;Venkataraman, Chandrasekhar
细胞跟踪算法，自动化和系统化的分析时间推移图像数据集的细胞是一个不可或缺的工具，在建模和理解的细胞现象。在这项研究中，我们提出了一个理论框架和算法的全细胞跟踪。在这项工作中，我们认为，“跟踪”是等同于从静态图像数据集的整个细胞数据（形态）的动态重建。我们工作的新奇在于，跟踪算法是由细胞运动的模型驱动的。这个模型可以被看作是一个简化的最近开发的物理意义的细胞运动模型。由此产生的问题是最优控制的几何发展规律，我们讨论的制定和数值逼近的最优控制问题。这项工作的总体目标是设计一个框架内的细胞跟踪恢复的数据反映了物理的前向模型。一些数值模拟，说明了我们的方法的适用性。(C)2015作者爱思唯尔公司出版这是一篇在CC BY许可证下的开放获取文章
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. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license