The automated measurement of foci in fluorescence microscopy

荧光显微镜中焦点的自动测量

• 批准号: 8938556
• 负责人: stuart j austin
• 金额: $ 7.97万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8938556
• 关键词: Bacteria; Cells; Chromosomes; Collaborations; Color; Computer Analysis; Computer software; Data; Data Collection; Denmark; Development; Escherichia coli; Fluorescence; Fluorescence Microscopy; Image; Image Analysis; Individual; Information Systems; Laboratories; Light; Measurement; Measures; Minor; Plasmids; Population; Positioning Attribute; Radial; System; Technology; Universities; analytical tool; cellular imaging; meetings; programs; trend

In collaboration with the laboratory of Dr, Flemming Hansen, Technical University of Denmark, we have developed a fully automated cell recognition and fluorescent focus-measuring program in the form of a macro within the image analysis program Image Pro Plus. This has been very successful in the basic tasks of detecting fluorescent foci formed by plasmids and specific chromosomal loci in cells of the bacterium Escherichia coli. As our needs for analysis of fluorescent images become more demanding, we continue to develop and adapt this system to meet them. We have developed an analytical tool "Inspect" that facilitates the analysis of images that have two color fluorescence information. In conjunction with the data collection programs, we have developed an array of spreadsheet programs to analyze and portray the data. We have completed a major new thrust in the development of the image analysis software. This allows the automated identification of multiple classes of cells in various states of division, and of foci that are dividing etc. These cells can then be inspected directly as a sub-class of images extracted for inspection. New sub-classes can then be defined and analyzed with seamless switching between the numerical data and the individual cell images. This allows us to analyze large populations in far more detail than was previously possible. This year we developed extensive software to handle the extended data collecting capability that we developed in 2011.Special emphasis has been laid on the ability to analize the cell short axis data and to project distributions of markers to the radial axis. This allows us to predict. the dynamic form of the replicating and segregating chromosomes in 3D.

我们与丹麦技术大学Flemming Hansen博士的实验室合作，在图像分析程序image Pro Plus中以宏的形式开发了全自动细胞识别和荧光聚焦测量程序。这在检测大肠杆菌细胞中由质粒和特定染色体位点形成的荧光灶的基本任务中非常成功。随着我们对荧光图像分析的需求越来越高，我们继续开发和适应这个系统来满足他们。我们开发了一种分析工具“Inspect”，便于分析具有两种颜色荧光信息的图像。结合数据收集程序，我们开发了一系列电子表格程序来分析和描绘数据。我们已经完成了图像分析软件开发的一个重要的新推力。这样就可以自动识别处于不同分裂状态的多类细胞，以及正在分裂的病灶等。然后可以直接检查这些细胞，作为提取用于检查的图像的子类。然后可以通过在数值数据和单个细胞图像之间的无缝切换来定义和分析新的子类。这使我们能够比以前更详细地分析大量人口。今年，我们开发了广泛的软件来处理我们在2011年开发的扩展数据收集功能。特别强调了分析细胞短轴数据和将标记分布投影到径向轴的能力。这使我们能够预测。染色体复制和分离的三维动态形式。