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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Cell tracking in microscopic video using matching and linking of bipartite graphs
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Cell tracking in microscopic video using matching and linking of bipartite graphs

机译：使用二部图的匹配和链接在微观视频中进行细胞跟踪

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摘要

Automated visual tracking of cells from video microscopy has many important biomedical applications. In this paper, we track human monocyte cells in a fluorescent microscopic video using matching and linking of bipartite graphs. Tracking of cells over a pair of frames is modeled as a maximum cardinality minimum weight matching problem for a bipartite graph with a novel cost function. The tracking results are further refined using a rank-based filtering mechanism. Linking of cell trajectories over different frames are achieved through composition of bipartite matches. The proposed solution does not require any explicit motion model, is highly scalable, and, can effectively handle the entry and exit of cells. Our tracking accuracy of (97.97 ± 0.94)% is superior than several existing methods [(95.66 ± 2.39)% [11], (94.42 ± 2.08)% [20], (81.22 ± 5.75)% [13], (78.31 ± 4.70)% [14]] and is highly comparable (98.20 ± 1.22)% to a recently published algorithm [26].
机译：通过视频显微镜对细胞进行自动视觉跟踪具有许多重要的生物医学应用。在本文中，我们使用二分图的匹配和链接在荧光显微视频中跟踪人单核细胞。对于具有新颖成本函数的二部图，将一对帧上的单元格跟踪建模为最大基数最小权重匹配问题。使用基于等级的过滤机制进一步完善跟踪结果。通过二分匹配的组成可以实现不同框架上细胞轨迹的链接。提出的解决方案不需要任何显式的运动模型，具有高度可伸缩性，并且可以有效地处理单元的进入和退出。我们的（97.97±0.94）％跟踪精度优于几种现有方法[（95.66±2.39）％[11]，（94.42±2.08）％[20]，（81.22±5.75）％[13]，（78.31± 4.70％[14]]，与最近发布的算法[26]高度可比（98.20±1.22）％。

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