Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ.
Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ.
复制标题
ImageJ中超分辨率结构化照明显微镜数据的开源图像重建。
DOI：
10.1038/ncomms10980
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发表时间：
2016-03-21
影响因子：
16.6
通讯作者：
Huser T
中科院分区：
文献类型：
--
作者：
Müller M;Mönkemöller V;Hennig S;Hübner W;Huser T
超分辨结构照明显微镜(SR-SIM)是一种重要的荧光显微镜工具。SR-SIM显微镜使用不同的照明模式执行多个图像采集，并将其重建为超分辨率图像。在其最常见的线性实现中，SR-SIM将空间分辨率提高一倍。对获取的广域图像数据进行数值重建，因此依赖于特定SR-SIM图像重建算法的软件实现。我们提供了airSIM，这是一个简单易用的插件，可以直接在ImageJ中为各种SR-SIM平台提供SR-SIM重建。对于开发自己的超分辨率结构照明显微镜实现的研究小组来说，Fair SIM消除了生成另一种重建算法实现的障碍。对于商业显微镜的用户，它为他们的数据提供了一个额外的、深入的分析选项，独立于特定的操作系统。作为一种模块化、开源的解决方案，随着SR-SIM领域的发展，airSIM可以很容易地进行调整、自动化和扩展。超分辨率结构照明显微镜(SR-SIM)数据集的重建通常依赖于商业软件。在这里，穆勒等人。提供一个开源的ImageJ插件，以便于从广泛的显微镜平台重建SR-SIM数据。
Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses. Reconstruction of super resolution structured illumination microscopy (SR-SIM) datasets typically relies upon commercial software. Here Müller et al. present an open-source ImageJ plugin to facilitate reconstruction of SR-SIM data from a broad range of microscopy platforms.