Belevich Ilya, Joensuu Merja, Kumar Darshan, Vihinen Helena, Jokitalo Eija
Electron Microscopy Unit, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
PLoS Biol. 2016 Jan 4;14(1):e1002340. doi: 10.1371/journal.pbio.1002340. eCollection 2016 Jan.
Understanding the structure-function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.
要在自然环境中理解细胞和细胞器的结构-功能关系,需要进行多维成像。随着多模态三维成像技术变得更加容易获取,对大型数据集进行有效的处理、可视化和分析正成为工作流程中的一个瓶颈。在此,我们展示了一个用于多维数据集的高性能分割和图像处理的新软件包,它改进并促进了对采集数据的充分利用和定量分析,该软件包可从一个专门网站免费获取。开源环境允许修改和插入新插件,以便根据特定需求定制程序。我们提供了用于处理、分割和分析光学和电子显微镜数据集的程序功能的实际示例,以及详细的教程,以便用户能够快速且全面地学习如何使用该程序。