Visualization and Computer Vision Laboratory, GE Global Research, Niskayuna, New York 12309, USA.
Annu Rev Biomed Eng. 2010 Aug 15;12:315-44. doi: 10.1146/annurev-bioeng-070909-105235.
The systems-level analysis of complex biological processes requires methods that enable the quantification of a broad range of phenotypical alterations, the precise localization of signaling events, and the ability to correlate such signaling events in the context of the spatial organization of the biological specimen. The goal of this review is to illustrate that, when combined with modern imaging platforms and labeling techniques, automated image analysis methods can provide such quantitative information. The article attempts to review necessary image analysis techniques as well as applications that utilize these techniques to provide the data that will enable systems-level biology. The text includes a review of image registration and image segmentation methods, as well as algorithms that enable the analysis of cellular architecture, cell morphology, and tissue organization. Various methods that enable the analysis of dynamic events are also presented.
系统水平分析复杂的生物过程需要能够定量广泛表型改变、精确定位信号事件，并能够在生物样本空间组织背景下关联这些信号事件的方法。本文的目的是说明，当与现代成像平台和标记技术结合使用时，自动化图像分析方法可以提供此类定量信息。本文尝试综述必要的图像分析技术以及利用这些技术提供数据以实现系统生物学的应用。文本包括对图像配准和图像分割方法的综述，以及用于分析细胞结构、细胞形态和组织组织的算法。还介绍了各种用于分析动态事件的方法。
