The automated measurement of foci in fluorecence microscopy

与丹麦工业大学Flemming Hansen博士的实验室合作，我们开发了一个完全自动化的细胞识别和荧光焦点测量程序，该程序在图像分析程序Image Pro Plus中以宏的形式存在。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取得了非常成功的成果。随着我们对荧光图像分析的需求变得越来越苛刻，我们继续开发和调整该系统以满足这些需求。我们正在开发一种分析工具Insight，它可以方便地分析具有两种颜色荧光信息的图像。结合数据收集程序，我们正在开发一系列电子表格程序来分析和描绘数据。我们最近在图像分析软件的开发方面完成了一项新的重大工作。这允许自动识别处于各种分割状态的多类细胞以及正在分割的焦点等。然后可以将这些细胞作为提取用于检查的图像的子类直接进行检查。然后可以定义和分析新的子类，并在数字数据和单个细胞图像之间进行无缝切换。这使我们能够比以前更认真地分析大量人口。

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 are developing an analytical tool Inspect that facilitates the analysis of images that have two color fluorescence information. In conjunction with the data collection programs, we are developing an array of spreadsheet programs to analyze and portray the data. We have very recently 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 analysed with seamless switching between the numberical data and the individual cell images. This allows us to analyse large populations in far more deteil than was previously possible.