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New robust algorithm for tracking cells in videos of drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures

机译:在果蝇时空细胞结构中寻找理想路径的新功能强大的果蝇形态发生视频中的细胞追踪算法

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In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions — first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.
机译:在本文中,我们提出了一种新的算法,用于在p形态发生过程中跟踪果蝇上皮组织的延时共聚焦显微镜电影中的细胞。我们将2D +时间视频视为3D静态图像,其中帧彼此堆叠,然后使用时空分割算法,获得有关表示细胞演化的时空3D管的信息。跟踪的主要思想是使用两个距离函数-第一个距离函数来自初始帧中的单元格,第二个距离函数来自分段边界。我们及时向后追踪细胞。第一个距离函数将后续构造的单元格轨迹吸引到初始框架中的单元格,第二个距离函数将其逼近分段管状结构的中心线。这使我们的跟踪算法对噪声和时空边界丢失具有鲁棒性。这种方法可以推广到3D +时间视频分析,其中时空管是4D对象。

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