A Survey of Visualization for Live Cell Imaging

A Survey of Visualization for Live Cell Imaging
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DOI:
10.1111/cgf.12784
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发表时间:
2017-01-01
影响因子:
2.5
通讯作者:
Errington, R. J.
Errington, R. J.
中科院分区:
计算机科学4区
文献类型:
--
作者:
Pretorius, A. J.;Khan, I. A.;Errington, R. J.

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活细胞成像是研究动态细胞行为的重要生物医学研究范式。虽然从图像中获得的表型数据很难探索和分析,但一些研究人员已经成功地通过可视化解决了这一问题。尽管如此,活细胞成像数据的可视化方法已被报告在一个特设和零碎的方式。这导致了一个知识缺口,生物学家和可视化开发人员很难评估不同可视化方法的优点和缺点,可视化研究人员也很难获得现有工作的概述,以确定研究重点。为了解决这一差距,我们首次从可视化研究的角度调查了现有的活细胞成像可视化方法。基于最近的可视化理论,我们进行了结构化的定性分析的可视化方法,包括表征域和数据,抽象任务,描述视觉编码和交互设计。根据我们的调查,我们确定并讨论了未来工作应解决的研究差距:活细胞成像的广泛分析背景;行为比较的重要性;与动态数据可视化的联系;不同数据模式的后果;交互式支持的缺点;以及,除了分析,表型数据和见解的呈现给其他利益相关者的价值。
Live cell imaging is an important biomedical research paradigm for studying dynamic cellular behaviour. Although phenotypic data derived from images are difficult to explore and analyse, some researchers have successfully addressed this with visualization. Nonetheless, visualization methods for live cell imaging data have been reported in an ad hoc and fragmented fashion. This leads to a knowledge gap where it is difficult for biologists and visualization developers to evaluate the advantages and disadvantages of different visualization methods, and for visualization researchers to gain an overview of existing work to identify research priorities. To address this gap, we survey existing visualization methods for live cell imaging from a visualization research perspective for the first time. Based on recent visualization theory, we perform a structured qualitative analysis of visualization methods that includes characterizing the domain and data, abstracting tasks, and describing visual encoding and interaction design. Based on our survey, we identify and discuss research gaps that future work should address: the broad analytical context of live cell imaging; the importance of behavioural comparisons; links with dynamic data visualization; the consequences of different data modalities; shortcomings in interactive support; and, in addition to analysis, the value of the presentation of phenotypic data and insights to other stakeholders.