Segmentation and quantitative analysis of individual cells in developmental tissues.
Segmentation and quantitative analysis of individual cells in developmental tissues.
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发育组织中单个细胞的分割和定量分析。
DOI：
10.1007/978-1-60327-292-6_16
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Lockett,StephenJ
中科院分区：
文献类型：
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作者：
Nandy,Kaustav;Kim,Jusub;McCullough,DeanP;McAuliffe,Matthew;Meaburn,KarenJ;Yamaguchi,TerryP;Gudla,PrabhakarR;Lockett,StephenJ
图像分析对于从生物图像中提取定量信息至关重要，并且被广泛使用，包括发育生物学的研究。该技术开始于从2D图像或3D图像堆栈中分割（描绘）感兴趣的对象，并且通常随后是对分割的对象的测量和分类。本章重点介绍分割任务，并在此解释ImageJ、MIPAV（医学图像处理、分析和可视化）和VisSeg的使用，这三个免费软件包可用于此目的。ImageJ和MIPAV非常通用，可用于各种应用。VisSeg是一种专门的工具，用于对图像和堆栈中的细胞和细胞核等对象执行高度准确和可靠的2D和3D分割。
Image analysis is vital for extracting quantitative information from biological images and is used extensively, including investigations in developmental biology. The technique commences with the segmentation (delineation) of objects of interest from 2D images or 3D image stacks and is usually followed by the measurement and classification of the segmented objects. This chapter focuses on the segmentation task and here we explain the use of ImageJ, MIPAV (Medical Image Processing, Analysis, and Visualization), and VisSeg, three freely available software packages for this purpose. ImageJ and MIPAV are extremely versatile and can be used in diverse applications. VisSeg is a specialized tool for performing highly accurate and reliable 2D and 3D segmentation of objects such as cells and cell nuclei in images and stacks.