FIB/SEM tomography segmentation by optical flow estimation

•An algorithm for FIB/SEM tomography dataset segmentation is presented.•The algorithm accurately binarizes reconstructions of porous samples.•Two previously segmented datasets are used for validation of the results.•The algorithm reaches an accuracy of up to 86.6%. 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.