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首页> 外文会议>Machine learning in medical imaging >Optimal Live Cell Tracking for Cell Cycle Study Using Time-Lapse Fluorescent Microscopy Images
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Optimal Live Cell Tracking for Cell Cycle Study Using Time-Lapse Fluorescent Microscopy Images

机译：使用延时荧光显微镜图像进行细胞周期研究的最佳活细胞追踪

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摘要

Cell cycle study using time-lapse fluorescent microscopy images is important for understanding the mechanisms of cell division and screening of anti-cancer drugs. Cell tracking is necessary for quantifying cell behaviors. However, the complex behaviors and similarity of individual cells in a dense population make the cell population tracking challenging. To deal with these challenges, we propose a novel tracking algorithm, in which the local neighboring information is introduced to distinguish the nearby cells with similar morphology, and the Interacting Multiple Model (IMM) filter is employed to compensate for cell migrations. Based on a similarity metric, integrating the local neighboring information, migration prediction, shape and intensity, the integer programming is used to achieve the most stable association between cells in two consecutive frames. We evaluated the proposed method on the high content screening assays of HeLa cancer cell populations, and achieved 92% average tracking accuracy.
机译：使用延时荧光显微镜图像进行细胞周期研究对于理解细胞分裂的机制和抗癌药物的筛选非常重要。细胞跟踪对于量化细胞行为是必需的。然而，在密集种群中单个细胞的复杂行为和相似性使得追踪细胞种群具有挑战性。为了应对这些挑战，我们提出了一种新颖的跟踪算法，其中引入了局部邻近信息以区分具有相似形态的附近细胞，并使用交互多模型（IMM）滤波器来补偿细胞迁移。基于相似性度量，将本地邻近信息，迁移预测，形状和强度进行集成，整数编程用于在两个连续帧中的单元之间实现最稳定的关联。我们在HeLa癌细胞群的高含量筛选测定中评估了所提出的方法，并实现了92％的平均跟踪准确性。

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  • 来源
    《Machine learning in medical imaging》|2010年|p.124-131|共8页
  • 会议地点 Beijing(CN);Beijing(CN);Beijing(CN);Beijing(CN)
  • 作者

    Fuhai Li; Xiaobo Zhou; Stephen T.C. Wong;

  • 作者单位

    Center for Bioengineering and Informatics, The Methodist Hospital Research Institute and Research Department of Radiology, The Methodist Hospital, Weill Cornell Medical College, Houston, TX 77030, U.S.A.;

    Center for Bioengineering and Informatics, The Methodist Hospital Research Institute and Research Department of Radiology, The Methodist Hospital, Weill Cornell Medical College, Houston, TX 77030, U.S.A.;

    Center for Bioengineering and Informatics, The Methodist Hospital Research Institute and Research Department of Radiology, The Methodist Hospital, Weill Cornell Medical College, Houston, TX 77030, U.S.A.;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 医用物理学;
  • 关键词

    cell tracking; voronoi tessellation; interacting multiple model; cell cycle progression; drug screening;

    机译：细胞跟踪； voronoi镶嵌相互作用的多个模型；细胞周期进程；药物筛选;

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