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GPU-accelerated ray-casting for 3D fiber orientation analysis

Shkarin, R. 1,2; Shkarina, S. 3; Weinhardt, V. 2,3; Surmenev, R. A.; Surmeneva, M. A.; Shkarin, A. 2; Baumbach, T. 2,3; Mikut, R. ORCID iD icon 1
1 Fakultät für Maschinenbau – Institut für Angewandte Informatik/Automatisierungstechnik (AIA), Karlsruher Institut für Technologie (KIT)
2 Laboratorium für Applikationen der Synchrotronstrahlung (LAS), Karlsruher Institut für Technologie (KIT)
3 Institut für Photonenforschung und Synchrotronstrahlung (IPS), Karlsruher Institut für Technologie (KIT)


Orientation analysis of fibers is widely applied in the fields of medical, material and life sciences. The orientation information allows predicting properties and behavior of materials to validate and guide a fabrication process of materials with controlled fiber orientation. Meanwhile, development of detector systems for high-resolution non-invasive 3D imaging techniques led to a significant increase in the amount of generated data per a sample up to dozens of gigabytes. Though plenty of 3D orientation estimation algorithms were developed in recent years, neither of them can process large datasets in a reasonable amount of time. This fact complicates the further analysis and makes impossible fast feedback to adjust fabrication parameters. In this work, we present a new method for quantifying the 3D orientation of fibers. The GPU implementation of the proposed method surpasses another popular method for 3D orientation analysis regarding accuracy and speed. The validation of both methods was performed on a synthetic dataset with varying parameters of fibers. Moreover, the proposed method was applied to perform orientation analysis of scaffolds with different fibrous micro-architecture studied with the synchrotron μCT imaging setup. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000123085
Veröffentlicht am 01.09.2020
DOI: 10.1371/journal.pone.0236420
Zitationen: 4
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Institut für Photonenforschung und Synchrotronstrahlung (IPS)
Laboratorium für Applikationen der Synchrotronstrahlung (LAS)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 29.07.2020
Sprache Englisch
Identifikator ISSN: 1932-6203
KITopen-ID: 1000123085
HGF-Programm 56.03.30 (POF III, LK 01) Soft Matter, Health and Life Sciences
Erschienen in PLOS ONE
Verlag Public Library of Science (PLoS)
Band 15
Heft 7
Seiten Article: e0236420
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