Quantifying Hygroscopic Deformation in Lignocellulosic Tissues: A DVC Tool Comparison
- Link:
- Autor/in:
- Verlag/Körperschaft:
- Universität Hamburg
- Erscheinungsjahr:
- 2024
- Medientyp:
- Datensatz
- Schlagwort:
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- nano-holotomography, DVC, digital volume correlation, Hygroscopic deformation, lignocellulosic tissues
- Beschreibung:
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Reconstructed datasets of 3D nano-tomography images containing few cells of Hura crepitans fruit tissue, Pinus jeffreyi sclereid cells, a Marantochloa leucantha sclerenchyma fibre sheath and Pinus syvlestris latewood. Each sample type contains a wet state image (rh90/rh95) and a dry state image (rh0). The deformation between the states is calculated via digital volume correlations using Avizo, elastix and MBS-3D-OptFlow with the goal to identify the anisotropic hygroscopic shrinkage of the samples as well as the accuracy of the corresponding approach.
- LH and FS: DFG, German Research Foundation; HE 9048/1-1); LH: European Social Fund and the Ministry of Science, Research and the Arts Baden-Württemberg within the framework of the 'Margarete von Wrangell Habilitation Programme'; KU, TM, TS: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy— EXC-2193/1–390951807; TMK, BZ-P: ErUM-Data Verbundprojekt 'KI4D4E: Ein KI-basiertes Framework für die Visualisierung und Auswertung der massiven Datenmengen der 4D-Tomographie für Endanwender von Beamlines' which is funded by the Bundesministerium für Bildung und Forschung (BMBF, Förderkennzeichen 05D23CG1).
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- Lizenzen:
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- https://creativecommons.org/licenses/by/4.0/legalcode
- info:eu-repo/semantics/openAccess
- Quellsystem:
- Forschungsdatenrepositorium der UHH
Interne Metadaten
- Quelldatensatz
- oai:fdr.uni-hamburg.de:16522