Focused ion beam/scanning electron microscopy tomography (FIB/SEM tomography) is the method of choice for the tomographic reconstruction of mesoporous materials systems in various fields such as batteries, fuel cells, filter applications or composite materials. However, due to so called shine-through artifacts in FIB/SEM tomographies of porous materials, their segmentation into pore space and solid material is a nontrivial task. Here, an optical flow-based method that utilizes shine-through artifacts for segmentation is introduced. Subsequently, the performance of the method is discussed by means of tomographic datasets of a polymer electrolyte fuel cell catalyst layer and a lithium ion battery composite electrode. Previous, manual segmentations of these datasets allow the evaluation of the results - for the catalyst layer an accuracy of 86.6% and a precision of 84.0% is reached. In both cases, the optical flow-based approach gives significantly better results than comparable segmentations obtained from gray-value threshold binarization.

中文翻译：

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通过光流估计进行 FIB/SEM 断层扫描分割

聚焦离子束/扫描电子显微镜断层扫描（FIB/SEM 断层扫描）是各种领域中介孔材料系统断层扫描重建的首选方法，例如电池、燃料电池、过滤器应用或复合材料。然而，由于多孔材料的 FIB/SEM 层析成像中所谓的透光伪影，将它们分割成孔隙空间和固体材料是一项重要的任务。在这里，介绍了一种利用透光伪影进行分割的基于光流的方法。随后，通过聚合物电解质燃料电池催化剂层和锂离子电池复合电极的断层扫描数据集讨论了该方法的性能。以前，这些数据集的手动分割允许对结果进行评估——催化剂层的准确度为 86。6%，精度达到 84.0%。在这两种情况下，基于光流的方法比从灰度值阈值二值化获得的可比较分割给出了明显更好的结果。