Cell TypeAnalyzer:一个灵活的Fiji/ImageJ插件,可根据用户定义的标准对细胞进行分类

Biological imaging Pub Date : 2022-05-20 eCollection Date: 2022-01-01 DOI:10.1017/S2633903X22000058
Ana Cayuela López, José A Gómez-Pedrero, Ana M O Blanco, Carlos Oscar S Sorzano
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引用次数: 0

摘要

摘要荧光显微镜技术在生命科学中许多生物过程的可视化和分析方面有了长足的发展。我们描述了一种称为细胞类型分析仪的半自动多功能工具,以避免根据细胞类型对细胞进行耗时且有偏见的手动分类。它由Fiji或ImageJ的开源插件组成,用于检测和分类2D图像中的细胞。我们的工作流程包括(a)图像预处理操作、数据空间校准和用于分析的感兴趣区域;(b) 将细胞与背景分离的分割(可选地包括帮助识别细胞的用户定义的预处理步骤);(c) 从每个单元提取特征;(d) 过滤器以选择相关单元格;(e) 定义要包括在不同单元格类型中的特定标准;(f) 细胞分类;以及(g)对结果进行灵活分析。我们的软件提供了一种模块化和灵活的策略,通过类似向导的图形用户界面来执行细胞分类,在该界面中,用户可以直观地完成分析的每个步骤。此程序可以批量模式应用于多个显微镜文件。一旦建立了分析,就可以在许多图像上自动有效地执行分析。该插件不需要任何编程技能,可以在许多不同的采集设置中分析细胞。
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Cell-TypeAnalyzer: A flexible Fiji/ImageJ plugin to classify cells according to user-defined criteria.

Fluorescence microscopy techniques have experienced a substantial increase in the visualization and analysis of many biological processes in life science. We describe a semiautomated and versatile tool called Cell-TypeAnalyzer to avoid the time-consuming and biased manual classification of cells according to cell types. It consists of an open-source plugin for Fiji or ImageJ to detect and classify cells in 2D images. Our workflow consists of (a) image preprocessing actions, data spatial calibration, and region of interest for analysis; (b) segmentation to isolate cells from background (optionally including user-defined preprocessing steps helping the identification of cells); (c) extraction of features from each cell; (d) filters to select relevant cells; (e) definition of specific criteria to be included in the different cell types; (f) cell classification; and (g) flexible analysis of the results. Our software provides a modular and flexible strategy to perform cell classification through a wizard-like graphical user interface in which the user is intuitively guided through each step of the analysis. This procedure may be applied in batch mode to multiple microscopy files. Once the analysis is set up, it can be automatically and efficiently performed on many images. The plugin does not require any programming skill and can analyze cells in many different acquisition setups.

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