Institute of Structural and Molecular Biology, Department of Chemistry, University College London, London, United Kingdom.
Department of Chemistry, University College London, London, United Kingdom.
PLoS One. 2023 Oct 5;18(10):e0285691. doi: 10.1371/journal.pone.0285691. eCollection 2023.
Introducing SimpliPyTEM, a Python library and accompanying GUI that simplifies the post-acquisition evaluation of transmission electron microscopy (TEM) images, helping streamline the workflow. After an imaging session, a folder of image and/or video files, typically containing low contrast and large file size 32-bit images, can be quickly processed via SimpliPyTEM into high-quality, high-contrast.jpg images with suitably sized scale bars. The app can also generate HTML or PDF files containing the processed images for easy viewing and sharing. Additionally, SimpliPyTEM specifically focuses on in situ TEM videos, an emerging field of EM involving the study of dynamic processes whilst imaging. The package allows fast data processing into preview movies, averages, image series, or motion-corrected averages. The accompanying Python library offers many standard image processing methods, all simplified to a single command, plus a module to analyse particle morphology and population. This latter application is particularly useful for life sciences investigations. User-friendly tutorials and clear documentation are included to help guide users through the processing and analysis. We invite the EM community to contribute to and further develop this open-source package.
介绍 SimpliPyTEM,这是一个 Python 库和配套的图形用户界面,用于简化透射电子显微镜(TEM)图像的后获取评估,帮助简化工作流程。在成像会话之后,可以通过 SimpliPyTEM 将包含低对比度和大文件大小 32 位图像的文件夹的图像和/或视频文件快速处理成高质量、高对比度的.jpg 图像,并带有适当大小的比例尺。该应用程序还可以生成 HTML 或 PDF 文件,其中包含处理后的图像,以便于查看和共享。此外,SimpliPyTEM 特别关注原位 TEM 视频,这是一个新兴的 EM 领域,涉及在成像过程中研究动态过程。该软件包允许快速将数据处理成预览电影、平均值、图像序列或运动校正平均值。配套的 Python 库提供了许多标准的图像处理方法,都简化为单个命令,外加一个用于分析颗粒形态和群体的模块。后者在生命科学研究中特别有用。包含用户友好的教程和清晰的文档,以帮助指导用户完成处理和分析。我们邀请 EM 社区为这个开源软件包做出贡献并进一步开发它。