Department of Biomedical Engineering, Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, China.
State Key Laboratory of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University, Hangzhou, 310027, China.
Microsc Res Tech. 2020 Sep;83(9):1056-1065. doi: 10.1002/jemt.23496. Epub 2020 Apr 23.
With the development of super-resolution fluorescence microscopy, complex dynamic processes in living cells can be observed and recorded with unprecedented temporal and spatial resolution. Single particle tracking (SPT) is the most important step to explore the relationship between the spatio-temporal dynamics of subcellular molecules and their functions. Although previous studies have developed SPT algorithms to quantitatively analyze particle dynamics in cell, traditional tracking methods have poor performance when dealing with intersecting trajectories. This can be attributed to two main reasons: (a) they do not have point compensation process for overlapping objects; (b) they use inefficient motion prediction models. In this paper, we present a novel fan-shaped tracker (FsT) algorithm to reconstruct the trajectories of subcellular vesicles in living cells. We proposed a customized point compensation method for overlapping objects based on the fan-shaped motion trend of the particles. Furthermore, we validated the performance of the FsT in both simulated time-lapse movies with variable imaging quality and in real vesicle moving images. Meanwhile, we compared the performance of FsT with other five state-of-the-art tracking algorithms by using commonly defined measures. The results showed that our FsT achieves better performance in high signal-to-noise ratio conditions and in tracking of overlapping objects. We anticipate that our FsT method will have vast applications in tracking of moving objects in cell.
随着超分辨率荧光显微镜技术的发展，人们可以以前所未有的时间和空间分辨率观察和记录活细胞中的复杂动态过程。单粒子跟踪（SPT）是探索亚细胞分子的时空动力学与其功能之间关系的最重要步骤。尽管先前的研究已经开发出 SPT 算法来定量分析细胞中粒子的动力学，但传统的跟踪方法在处理轨迹交叉时性能不佳。这可以归因于两个主要原因：（a）它们没有重叠物体的点补偿过程；（b）它们使用效率低下的运动预测模型。在本文中，我们提出了一种新颖的扇形跟踪（FsT）算法，用于重建活细胞中亚细胞囊泡的轨迹。我们针对基于粒子扇形运动趋势的重叠物体提出了一种定制的点补偿方法。此外，我们在具有不同成像质量的模拟延时电影和真实囊泡运动图像中验证了 FsT 的性能。同时，我们使用常用的定义指标将 FsT 的性能与其他五种最先进的跟踪算法进行了比较。结果表明，我们的 FsT 在高信噪比条件下和跟踪重叠物体方面表现更好。我们预计我们的 FsT 方法将在细胞中跟踪运动物体方面有广泛的应用。
