@misc{sardhara_role_of_2024, 
author={Sardhara, T., Shkurmanov, A., Li, Y., Shi, S., Cyron, C.J., Aydin, R.C., Ritter, M.},
title={Role of slice thickness quantification in the 3D reconstruction of FIB tomography data of nanoporous materials},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.ultramic.2023.113878},
abstract = {In focused ion beam (FIB) tomography, a combination of FIB with a scanning electron microscope (SEM) is used for collecting a series of planar images of the microstructure of nanoporous materials. These planar images serve as the basis for reconstructing the three-dimensional microstructure through segmentation algorithms. However, the assumption of a constant distance between consecutively imaged sections is generally invalid due to random variations in the FIB milling process. This variation complicates the accurate reconstruction of the three-dimensional microstructure. Using synthetic FIB tomography data, we present an algorithm that repositions slices according to their actual thickness and interpolates the results using machine learning-based methods. We applied our algorithm to real datasets, comparing two standard approaches of microstructure reconstruction: on-the-fly via image processing and ruler-based via sample structuring. Our findings indicate that the ruler-based method, combined with our novel slice repositioning and interpolation algorithm, exhibits superior performance in reconstructing the microstructure.},
note = {Online available at: \url{https://doi.org/10.1016/j.ultramic.2023.113878} (DOI). Sardhara, T.; Shkurmanov, A.; Li, Y.; Shi, S.; Cyron, C.; Aydin, R.; Ritter, M.: Role of slice thickness quantification in the 3D reconstruction of FIB tomography data of nanoporous materials. Ultramicroscopy. 2024. vol. 256, 113878. DOI: 10.1016/j.ultramic.2023.113878}}