A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.
A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.
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DOI：
10.1371/journal.pone.0027315
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Kruse C
中科院分区：
文献类型：
--
作者：
Rapoport DH;Becker T;Madany Mamlouk A;Schicktanz S;Kruse C
自动显微镜是目前唯一可以非侵入性和无标记观察复杂多细胞过程（例如细胞迁移、细胞周期和细胞分化）的方法。从时间序列的显微照片中提取生物信息需要识别每个细胞，并通过连续的显微快照进行跟踪。虽然最近尝试自动化这一过程导致不断提高细胞检测率，手动识别相同的细胞仍然是最可靠的技术。然而，其繁琐和主观的性质阻止了跟踪成为一个标准化的工具，用于研究细胞培养。在这里，我们提出了一种新的方法来实现自动化的细胞跟踪与手动跟踪的可靠性。在此之前，自动化细胞跟踪无法与人工跟踪的可靠性相媲美，因为与人类解决这一任务的方式相比，没有一种算法具有独立的质量控制机制;它们错过了验证。因此，我们不是试图提高小区检测或跟踪率，而是从自动检查跟踪结果并仅接受那些高可信度的结果的想法出发，而拒绝所有其他结果。该验证算法通过系统搜索跟踪误差而独立于小区检测和跟踪的质量工作。它只基于非常一般的假设时空连续的细胞路径。虽然传统的跟踪通常旨在产生有关单个细胞的谱系信息，但经过验证的细胞跟踪算法的自然结果是一组完整的，但通常不连接的细胞路径，即从有丝分裂到有丝分裂的细胞记录。这是验证算法将完整路径作为拒绝/接受单元的事实的结果。所得到的一组完整路径可以用于自动提取具有高可靠性和统计显著性的重要生物参数。这些包括生命/周期时间和细胞面积的分布，以及细胞分裂和运动分析的对称性。因此，新算法允许以前所未有的准确度对细胞培养进行量化和参数化。为了评估我们的验证算法，手动创建了两个大型参考数据集。这些数据集包括来自大鼠的超过320，000个未染色的成体胰腺干细胞，包括2592个有丝分裂事件。参考数据集指定每个细胞的位置和形状，并将每个细胞分配到其系谱树的正确分支。我们提供这些参考数据集供他人免费使用，作为未来改进自动跟踪方法的基准。
Automated microscopy is currently the only method to non-invasively and label-free observe complex multi-cellular processes, such as cell migration, cell cycle, and cell differentiation. Extracting biological information from a time-series of micrographs requires each cell to be recognized and followed through sequential microscopic snapshots. Although recent attempts to automatize this process resulted in ever improving cell detection rates, manual identification of identical cells is still the most reliable technique. However, its tedious and subjective nature prevented tracking from becoming a standardized tool for the investigation of cell cultures. Here, we present a novel method to accomplish automated cell tracking with a reliability comparable to manual tracking. Previously, automated cell tracking could not rival the reliability of manual tracking because, in contrast to the human way of solving this task, none of the algorithms had an independent quality control mechanism; they missed validation. Thus, instead of trying to improve the cell detection or tracking rates, we proceeded from the idea to automatically inspect the tracking results and accept only those of high trustworthiness, while rejecting all other results. This validation algorithm works independently of the quality of cell detection and tracking through a systematic search for tracking errors. It is based only on very general assumptions about the spatiotemporal contiguity of cell paths. While traditional tracking often aims to yield genealogic information about single cells, the natural outcome of a validated cell tracking algorithm turns out to be a set of complete, but often unconnected cell paths, i.e. records of cells from mitosis to mitosis. This is a consequence of the fact that the validation algorithm takes complete paths as the unit of rejection/acceptance. The resulting set of complete paths can be used to automatically extract important biological parameters with high reliability and statistical significance. These include the distribution of life/cycle times and cell areas, as well as of the symmetry of cell divisions and motion analyses. The new algorithm thus allows for the quantification and parameterization of cell culture with unprecedented accuracy. To evaluate our validation algorithm, two large reference data sets were manually created. These data sets comprise more than 320,000 unstained adult pancreatic stem cells from rat, including 2592 mitotic events. The reference data sets specify every cell position and shape, and assign each cell to the correct branch of its genealogic tree. We provide these reference data sets for free use by others as a benchmark for the future improvement of automated tracking methods.
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影响因子：
4.3
作者：
Dingli D;Traulsen A;Michor F
通讯作者：
Michor F
影响因子：
4.3
作者：
Al-Kofahi, O;Radke, RJ;Roysam, B
通讯作者：
Roysam, B
DOI：
10.1007/978-1-61779-108-6_6
发表时间：
2011-01-01
期刊：
MAMMALIAN CELL VIABILITY: METHODS AND PROTOCOLS
影响因子：
--
作者：
Ke, Ning;Wang, Xiaobo;Abassi, Yama A.
通讯作者：
Abassi, Yama A.
影响因子：
2.2
作者：
Krusea, Charli;Kajahn, Jennifer;Wedel, Thilo
通讯作者：
Wedel, Thilo
影响因子：
6.6
作者：
Gorjup, Erwin;Danner, Sandra;von Briesen, Hagen
通讯作者：
von Briesen, Hagen