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A SIMULTANEOUS LOCALIZATION AND TRACKING METHOD FOR A WORM TRACKING SYSTEM

机译:WORM跟踪系统的同时定位和跟踪方法

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The idea of worm tracking refers to the path analysis of Caenorhabditis elegans nematodes and is an important tool in neurobiology which helps to describe their behavior. Knowledge about nematode behavior can be applied as a model to study the physiological addiction process or other nervous system processes in animals and humans. Tracking is performed by using a special manipulator positioning a microscope with a camera over a dish with an observed individual. In the paper, the accuracy of a nematode's trajectory reconstruction is investigated. Special attention is paid to analyzing errors that occurred during the microscope displacements. Two sources of errors in the trajectory reconstruction are shown. One is due to the difficulty in accurately measuring the microscope shift, the other is due to a nematode displacement during the microscope movement. A new method that increases path reconstruction accuracy based only on the registered sequence of images is proposed. The method Simultaneously Localizes And Tracks (SLAT) the nematodes, and is robust to the positioning system displacement errors. The proposed method predicts the nematode position by using NonParametric Regression (NPR). In addition, two other methods of the SLAT problem are implemented to evaluate the NPR method. The first consists in ignoring the nematode displacement during microscope movement, and the second is based on a Kalman filter. The results suggest that the SLAT method based on nonparametric regression gives the most promising results and decreases the error of trajectory reconstruction by 25% compared with reconstruction based on data from the positioning system.
机译:蠕虫跟踪的概念是指秀丽隐杆线虫线虫的路径分析,是神经生物学中有助于描述其行为的重要工具。关于线虫行为的知识可以用作研究动物和人类的生理成瘾过程或其他神经系统过程的模型。通过使用特殊的操纵器来进行跟踪,该操纵器将带有照相机的显微镜放置在有被观察者的盘子上。在本文中,研究了线虫轨迹重建的准确性。要特别注意分析显微镜移位期间发生的错误。示出了轨迹重建中的两个误差源。一种是由于难以精确测量显微镜的位移,另一种是由于显微镜移动过程中的线虫位移。提出了一种仅基于图像的配准序列来提高路径重建精度的新方法。该方法同时定位和跟踪线虫(SLAT),并且对定位系统位移误差具有鲁棒性。所提出的方法通过使用非参数回归(NPR)来预测线虫的位置。此外,还采用了SLAT问题的其他两种方法来评估NPR方法。第一个是忽略显微镜移动过程中线虫的位移,第二个是基于卡尔曼滤波器。结果表明,与基于定位系统数据的重建相比,基于非参数回归的SLAT方法提供了最有希望的结果,并将轨迹重建的误差降低了25%。

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