本文为美国明尼苏达大学（作者：MONISHA KODI SHIVANNA）的硕士论文，共55页。

细胞是生物体的基本结构、功能和生物功能单元。细胞通常被称为“生命的基本组成部分”，因为它们能够独立复制。细胞和细胞过程的研究在生物体的研究中是必不可少的。粒子检测和跟踪对于理解活细胞中发生的过程起着至关重要的作用。生物过程涉及复杂的动态机制，这使得分析和从观测中得出结论变得非常困难。

技术进步大大提高了可收集数据的质量和数量：现在，纳米分辨率的粒子可以在相当长的时间间隔内以复杂的细节成像，从而使我们能够在细胞和分子水平上获得有关生物过程的信息。荧光探针的广泛应用揭示了不同粒子及其在各种过程中的作用。然而，有许多因素影响了我们无法控制的过程，从而阻碍了我们成功地检测和固定粒子。由于存在大量的粒子，这些粒子在大小、性质、出现密度、荧光、运动性质等方面都有所不同，因此不可能有一个统一的检测和跟踪算法为我们提供最准确的结果。由于存在大量的独立参数，其中一些参数是上述提到的，这使得模拟过程变得困难，阻碍了我们对过程的理解，并从中得出结论。本文主要研究了几种最流行的检测和跟踪算法，最后，将所开发的检测与跟踪算法应用于双向轴索货物运输的研究。包含跟踪算法的结果视频已作为补充视频1提交。

Cells are the basic structural, functionaland biological functional unit in living organisms. Cells are usually called“fundamental building blocks of life” due to their ability to replicateindependently. The study of cells and cell processes is imperative in the studyof living organisms. Particle detection and tracking plays a vital role inunderstanding the processes that occur in living cells. Biological processesinvolve complex and dynamic machinery which makes it very difficult to analyzeand draw conclusions from the observations. Technological advancements havesignificantly improved the quality and quantity of data that can be collected:particles with nanometer resolution can now be imaged with intricate detailsover a significant interval of time, thus providing us access to informationabout the biological processes at a cellular and molecular level. The extensiveuse of fluorescent probes sheds light on the different particles and theirroles in the various processes. However, there are a lot of factors whichaffect the processes that are not under our control thereby inhibiting us fromsuccessfully detecting and tacking particles. The presence of a plethora ofparticles which vary in size, nature, density of occurrence, fluorescence,nature of motion etc. makes it impossible to have a unified detection andtracking algorithm that can provide us with the most accurate results. Thepresence of a wide number of independent parameters some of which are mentionedabove makes it hard to simulate a process and hinders the understanding ofprocesses and drawing conclusions from them. This study mainly focuses onsummarizing some of the most popular detection and tracking algorithms. Towardsthe end, the developed detection and tracking algorithm is applied to studybidirectional axonal cargo transport. A video containing the result of thetracking algorithm has been submitted as Supplementary Video 1.