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Quantitative comparison of segmentation algorithms for FIB‐SEM images of porous media
Author(s) -
SALZER M.,
PRILL T.,
SPETTL A.,
JEULIN D.,
SCHLADITZ K.,
SCHMIDT V.
Publication year - 2015
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12182
Subject(s) - focused ion beam , segmentation , scanning electron microscope , voxel , computer science , materials science , high fidelity , beam (structure) , artificial intelligence , algorithm , microscopy , optics , computer vision , ion , physics , acoustics , composite material , quantum mechanics
Summary Focused ion beam tomography has proven to be capable of imaging porous structures on a nano‐scale. However, due to shine‐through artefacts, common segmentation algorithms often lead to severe dislocation of individual structures in z ‐direction. Recently, a number of approaches have been developed, which take into account the specific nature of focused ion beam‐scanning electron microscope images for porous media. In the present study, we analyse three of these approaches by comparing their performance based on simulated focused ion beam‐scanning electron microscope images. Performance is measured by determining the amount of misclassified voxels as well as the fidelity of structural characteristics. Based on this analysis we conclude that each algorithm has certain strengths and weaknesses and we determine the scenarios for which each approach might be the best choice