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Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography
View ORCID ProfileIllia Horenko, Lukas Pospisil, Edoardo Vecchi, Steffen Albrecht, Alexander Gerber, Beate Rehbock, View ORCID ProfileAlbrecht Stroh, View ORCID ProfileSusanne Gerber
doi: https://doi.org/10.1101/2021.08.10.455778
Illia Horenko
1USI Lugano, Faculty of Informatics, Via G. Buffi 13, TI-6900 Lugano, Switzerland
Lukas Pospisil
2VSB Ostrava, Department of Mathematics, Ludvika Podeste 1875/17 708 33 Ostrava, Czech Republic
Edoardo Vecchi
1USI Lugano, Faculty of Informatics, Via G. Buffi 13, TI-6900 Lugano, Switzerland
Steffen Albrecht
1USI Lugano, Faculty of Informatics, Via G. Buffi 13, TI-6900 Lugano, Switzerland
3Institute of Physiology, University Medical Center of the Johannes Gutenberg-University Mainz, Hanns-Dieter-Huesch-Weg 19, 55128 Mainz, Germany
Alexander Gerber
4Institute of Occupational Medicine, Faculty of Medicine, GU Frankfurt, Theodor-Stern-Kai 7, Haus 9b, 60590 Frankfurt am Main, Germany
Beate Rehbock
5Lung Radiology Center Berlin, Bismarckstr. 45-47, 10627 Berlin, Germany
Albrecht Stroh
6Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg-University Mainz, Hanns-Dieter-Huesch-Weg 19, 55128 Mainz, Germany
Susanne Gerber
7Institute for Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, 55128 Mainz, Germany
Posted August 11, 2021.
Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography
Illia Horenko, Lukas Pospisil, Edoardo Vecchi, Steffen Albrecht, Alexander Gerber, Beate Rehbock, Albrecht Stroh, Susanne Gerber
bioRxiv 2021.08.10.455778; doi: https://doi.org/10.1101/2021.08.10.455778
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