Trabuco João R C, Martins Sofia Aires M, Prazeres Duarte Miguel F
IBB - Institute for Biotechnology and Bioengineering, Lisbon, Portugal.
Methods Mol Biol. 2015;1272:143-72. doi: 10.1007/978-1-4939-2336-6_11.
Live-cell assays used in GPCR research often rely on fluorescence techniques that generate large amounts of raw image data. Consequently, the capacity to accurately and timely extract useful information from image and video data has become more and more important. Image J is an open-source program that provides powerful tools with a simple interface designed to fit the needs of image analysis of most researchers. In this chapter, Image J routines to extract information from individual cells in a calcium GPCR assay are described. In these routines, individual cells in the same image/video data can be separated using either a progressive threshold or a local threshold method. Both methods can be optimized to either a maximum number of selection or maximum area selected resulting in conceptually distinct selections.
GPCR研究中使用的活细胞分析通常依赖于能生成大量原始图像数据的荧光技术。因此，从图像和视频数据中准确、及时地提取有用信息的能力变得越来越重要。Image J是一个开源程序，它提供了强大的工具，其界面简单，旨在满足大多数研究人员的图像分析需求。在本章中，将描述在钙GPCR分析中从单个细胞提取信息的Image J程序。在这些程序中，可以使用渐进阈值法或局部阈值法分离同一图像/视频数据中的单个细胞。这两种方法都可以针对选择的最大数量或选择的最大面积进行优化，从而产生概念上不同的选择结果。
