Correction: Sinchuk et al. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936
by
, and
Yuriy Sinchuk
1,*, 
Pierre Kibleur
2,3,
Jan Aelterman
3,4,5,
Matthieu N. Boone
3,5
and
Wim Van Paepegem
1 1
Department of Materials Science and Engineering, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 46, 9052 Zwijnaarde, Belgium
2
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium
3
Center for X-ray Tomography (UGCT), Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium
4
Department of Telecommunications and Information Processing–Image Processing and Interpretation, Faculty of Engineering and Architecture, Ghent University—IMEC, Sint-Pietersnieuwstraat 41, 9000 Gent, Belgium
5
Department of Physics and Astronomy, Faculty of Sciences, Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium
*
Author to whom correspondence should be addressed.
Materials 2022, 15(22), 8168; https://doi.org/10.3390/ma15228168
Submission received: 23 October 2020
/
Accepted: 5 November 2021
/
Published: 17 November 2022
(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)
We would like to change the authors’ affiliation on the recent published paper [1] from:
Yuriy Sinchuk 1,*, Pierre Kibleur 2, Jan Aelterman 3, Matthieu N. Boone 4 and Wim Van Paepegem 1
1 Department of Materials Science and Engineering, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 46, 9052 Zwijnaarde, Belgium; [email protected]
2 Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium; [email protected]
3 Department of Telecommunications and information processing, Faculty of Engineering and Architecture, Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium; [email protected]
4 Department of Physics and astronomy, Faculty of Sciences, Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium; [email protected]
* Correspondence: [email protected]
to the correct version, as follows:
Yuriy Sinchuk 1,*, Pierre Kibleur 2,3, Jan Aelterman 3,4,5, Matthieu N. Boone 3,5 and Wim Van Paepegem 1
1 Department of Materials Science and Engineering, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 46, 9052 Zwijnaarde, Belgium; [email protected]
2 Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium; pierre.[email protected]
3 Center for X-ray Tomography (UGCT), Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium; [email protected] (J.A.); [email protected] (M.N.B.)
4 Department of Telecommunications and Information Processing–Image Processing and Interpretation, Faculty of Engineering and Architecture, Ghent University—IMEC, Sint-Pietersnieuwstraat 41, 9000 Gent, Belgium
5 Department of Physics and Astronomy, Faculty of Sciences, Ghent University, Proeftuinstraat 86, 9000 Gent, Belgium
* Correspondence: [email protected]
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.
Reference
- Sinchuk, Y.; Kibleur, P.; Aelterman, J.; Boone, M.N.; Van Paepegem, W. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936. [Google Scholar] [CrossRef] [PubMed] [Green Version]
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MDPI and ACS Style
Sinchuk, Y.; Kibleur, P.; Aelterman, J.; Boone, M.N.; Van Paepegem, W. Correction: Sinchuk et al. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936. Materials 2022, 15, 8168. https://doi.org/10.3390/ma15228168
AMA Style
Sinchuk Y, Kibleur P, Aelterman J, Boone MN, Van Paepegem W. Correction: Sinchuk et al. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936. Materials. 2022; 15(22):8168. https://doi.org/10.3390/ma15228168
Chicago/Turabian StyleSinchuk, Yuriy, Pierre Kibleur, Jan Aelterman, Matthieu N. Boone, and Wim Van Paepegem. 2022. "Correction: Sinchuk et al. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936" Materials 15, no. 22: 8168. https://doi.org/10.3390/ma15228168
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