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JAQUES, V. DU PLESSIS, A. ZEMEK, M. ŠALPLACHTA, J. ŠTUBIANOVÁ, Z. ZIKMUND, T. KAISER, J.
Originální název
Review of porosity uncertainty estimation methods in computed tomography dataset
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
X-ray computed tomography is widely used for non-destructive testing and analysis in a broad variety of fields. Its main usage is for 3D porosity identification and quantification. This can be achieved through the image segmentation of the reconstructed dataset which can have a huge impact on the porosity value. The most widely used segmentation algorithms are based on global thresholding, which takes the whole volume into account. To ensure a certain level of confidence and reproducibility of the porosity value, a thorough description of the workflow should be available with uncertainty estimation. This workflow description is often insufficient and the uncertainty missing according to a review of the literature. This work provides recommendations on how to report the processing steps for the porosity evaluation based on computed tomography data and reviews methods for the estimation of the porosity measurement uncertainty from the literature.
Klíčová slova
Global thresholding; Computed tomography; Uncertainty estimation; Results comparison; Porosity evaluation; Segmentation
Autoři
JAQUES, V.; DU PLESSIS, A.; ZEMEK, M.; ŠALPLACHTA, J.; ŠTUBIANOVÁ, Z.; ZIKMUND, T.; KAISER, J.
Vydáno
23. 8. 2021
Nakladatel
IOP Publishing
ISSN
0957-0233
Periodikum
Measurement Science and Technology
Ročník
32
Číslo
8
Stát
Spojené království Velké Británie a Severního Irska
Strany od
1
Strany do
17
Strany počet
URL
https://iopscience.iop.org/article/10.1088/1361-6501/ac1b40
Plný text v Digitální knihovně
http://hdl.handle.net/11012/201651
BibTex
@article{BUT172199, author="Victory {Jaques} and Anton {Du Plessis} and Marek {Zemek} and Jakub {Šalplachta} and Zuzana {Stravová} and Tomáš {Zikmund} and Jozef {Kaiser}", title="Review of porosity uncertainty estimation methods in computed tomography dataset", journal="Measurement Science and Technology", year="2021", volume="32", number="8", pages="1--17", doi="10.1088/1361-6501/ac1b40", issn="0957-0233", url="https://iopscience.iop.org/article/10.1088/1361-6501/ac1b40" }