Background Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high-resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Findings Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open-source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods and with newer Bayesian restoration approaches that we are developing. Conclusions Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments are not typically published. Publically available, high-quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data were processed with SIMToolbox, an open-source and freely available software solution for SIM.

中文翻译：

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用结构化照明显微镜和贝叶斯图像重建技术对超出衍射极限的组织和细胞进行成像。

背景结构照明显微镜（SIM）是光学荧光显微镜中的一类方法，可以同时实现光学切片和超分辨率效果。SIM是一种有用的方法，可用于对用常规荧光团标记的固定细胞或组织进行高分辨率成像，以及对表达荧光蛋白构建体的活细胞的动力学进行成像。在SIM中，一个人会获取一组具有变化照明图案的图像。随后用图像分析算法处理这组图像，以产生具有减少的散焦光（光学切片）和/或具有改善的分辨率（超分辨率）的图像。结果展示了五个完整的，免费提供的SIM数据集，包括原始数据和分析数据。我们报告使用开源软件进行图像采集和分析的方法，以及使用不同方法处理后的图像示例。我们使用已建立的光学切片SIM和超分辨率SIM方法以及正在开发的新型贝叶斯恢复方法来处理数据。结论正在积极开发各种用于SIM数据获取和处理的方法，但是通常不会发布来自SIM实验的完整原始数据。公开提供的高质量原始数据以及经过处理的结果示例将有助于研究人员开发SIM中的新方法。生物学家还将对我们获得的动物组织和细胞的高分辨率图像感兴趣。所有数据都使用SIMToolbox处理，SIMToolbox是SIM的开源和免费软件解决方案。