Rohde Florens, Braumann Ulf-Dietrich, Schmidt Matthias
Department of Isotope Biogeochemistry, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany.
Faculty of Engineering, Leipzig University of Applied Sciences (HTWK), Leipzig, Germany.
J Microsc. 2020 Jun 3. doi: 10.1111/jmi.12928.
The correlation of different microscopic imaging techniques alongside with microanalytical methods is crucial to better understand biological processes on a subcellular level. For that, micrographs and chemical maps exhibiting both, very different spatial resolution and field-of-view but also a highly multimodal content has to be co-registered. We developed the ImageJ/Fiji plug-in Correlia that provides an environment for handling multimodal correlative microscopy data. Several linear and nonlinear registration methods using either feature or area-based similarity measures can flexibly be cascaded to align and warp 2D microscopy data sets. The registration of data sets containing light- and electron micrographs as well as chemical maps acquired by secondary-ion mass spectroscopy and energy-dispersive X-ray spectroscopy is demonstrated. Correlia is an open-source tool developed particularly for the registration and analysis of highly multimodal 2D correlative microscopy data. LAY DESCRIPTION: If a microscopic object is imaged correlatively by two or more different microscopes the acquired micrographs will have to be overlaid accurately using an image-registration software. In cases of relatively similar image content creating such an overlay is straight-forward but what if the fields-of-view and resolutions of the micrographs differ significantly? What if there are distortions in a micrograph which have to be corrected before creating an overlay? What if furthermore a chemical map shall be overlaid that merely shows regions in which a certain chemical element is present? The rapidly increasing number of applications in correlative microscopy is calling for an easy-to-use and flexible image registration software that can deal with these challenges. Having that in mind, we developed Correlia, an ImageJ/Fiji plug-in that provides an environment for handling multimodal 2D correlative microscopy data-sets. It allows for creating overlays using different registration algorithms that can flexibly be cascaded. In this paper we describe what is happening 'under the hood' and give two example data-sets from microbiology which were registered using Correlia. Correlia is open source software and available from www.ufz.de/correlia - including introductory examples, as the authors would like to encourage other scientists to process their individual correlative microscopy data using Correlia.
将不同的显微成像技术与微分析方法相结合，对于在亚细胞水平上更好地理解生物过程至关重要。为此，必须对具有截然不同的空间分辨率和视野，且内容高度多模态的显微照片和化学图谱进行配准。我们开发了ImageJ/Fiji插件Correlia，它为处理多模态相关显微镜数据提供了一个环境。可以灵活地级联几种使用基于特征或基于区域的相似性度量的线性和非线性配准方法，以对齐和扭曲二维显微镜数据集。文中展示了包含光学和电子显微照片以及通过二次离子质谱和能量色散X射线光谱获得的化学图谱的数据集的配准过程。Correlia是一个开源工具，专门为高度多模态的二维相关显微镜数据的配准和分析而开发。层面描述：如果用两个或更多不同的显微镜对一个微观物体进行相关成像，那么使用图像配准软件必须精确地叠加所获取的显微照片。在图像内容相对相似的情况下，创建这样的叠加很简单，但如果显微照片的视野和分辨率有很大差异呢？如果在创建叠加之前必须校正显微照片中的畸变呢？此外，如果要叠加一个仅显示特定化学元素存在区域的化学图谱呢？相关显微镜应用的迅速增加，需要一个易于使用且灵活的图像配准软件来应对这些挑战。考虑到这一点，我们开发了Correlia，一个ImageJ/Fiji插件，它为处理多模态二维相关显微镜数据集提供了一个环境。它允许使用可以灵活级联的不同配准算法来创建叠加。在本文中，我们描述了其内部原理，并给出了两个使用Correlia配准的微生物学示例数据集。Correlia是开源软件，可从www.ufz.de/correlia获取，包括入门示例，因为作者希望鼓励其他科学家使用Correlia处理他们各自的相关显微镜数据。
