基于分段平稳多运动模型Kalman平滑器的显微镜时移图像中多微管跟踪
Multiple Microtubule Tracking in Microscopy Time-Lapse Images Using Piecewise-stationary Multiple Motion Model Kalman Smoother
摘要：
微管是固有的动态亚细胞丝状聚合物，其在细胞内通过马达蛋白在空间上组织，马达蛋白交联并移动微管。体外微管运动试验，其中电机连接到一个表面移动微管沿它，传统上已被用来研究运动功能。然而，微管-微管相互作用影响微管运动的方式在很大程度上尚未探索。为了解决这个问题，在体外微管运动性测定的时间推移图像系列获得使用全内反射荧光（TIRF）显微镜。归类为多目标跟踪（MOT）的一般问题，在这个项目中出现的具体挑战包括低特征多样性，动态不稳定性，微管运动模式的突然变化，以及它们的瞬时出现/消失。这项工作描述了一个新的应用分段固定多运动模型卡尔曼平滑（PMMS）建模个别微管运动趋势。为了评估该过程的能力并优化其超参数，首先使用模拟一系列延时图像的大型数据集。接下来，我们将其应用于来自真实数据的帧序列。我们的分析结果提供了微管速度的定量描述，反过来，列举了每帧微管-微管相互作用的发生。
英文摘要：
Microtubules are inherently dynamic sub-cellular filamentuous polymers that are spatially organized within the cell by motor proteins which cross-link and move microtubules. In-vitro microtubule motility assays, in which motors attached to a surface move microtubules along it, have been used traditionally to study motor function. However, the way in which microtubule-microtubule interactions affect microtubule movement remains largely unexplored. To address this question, time-lapse image series of in-vitro microtubule motility assays were obtained using total internal reflection fluorescence (TIRF) microscopy. Categorized as a general problem of multiple object tracking (MOT), particular challenges arising in this project include low feature diversity, dynamic instability, sudden changes in microtubules motility patterns, as well as their instantaneous appearance/disappearance. This work describes a new application of piecewise-stationary multiple motion model Kalman smoother (PMMS) for modeling individual microtubules motility trends. To both evaluate the capability of this procedure and optimize its hyper-parameters, a large dataset simulating the series of time-lapse images was used first. Next, we applied it to the sequence of frames from the real data. Results of our analyses provide a quantitative description of microtubule velocity which, in turn, enumerates the occurrence of microtubule-microtubule interactions per frame.
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