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Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
by
Sadeghinia, Mohammad Javad
, Terzano, Michele
, Skallerud, Bjørn
, Alberini, Riccardo
, Holzapfel, Gerhard A.
, Spagnoli, Andrea
in
639/166/985
/ 639/301/1034/1037
/ 639/301/930/12
/ Collagen
/ Fibers
/ Fourier transforms
/ Humanities and Social Sciences
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2024
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Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
by
Sadeghinia, Mohammad Javad
, Terzano, Michele
, Skallerud, Bjørn
, Alberini, Riccardo
, Holzapfel, Gerhard A.
, Spagnoli, Andrea
in
639/166/985
/ 639/301/1034/1037
/ 639/301/930/12
/ Collagen
/ Fibers
/ Fourier transforms
/ Humanities and Social Sciences
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2024
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Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
by
Sadeghinia, Mohammad Javad
, Terzano, Michele
, Skallerud, Bjørn
, Alberini, Riccardo
, Holzapfel, Gerhard A.
, Spagnoli, Andrea
in
639/166/985
/ 639/301/1034/1037
/ 639/301/930/12
/ Collagen
/ Fibers
/ Fourier transforms
/ Humanities and Social Sciences
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2024
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Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
Journal Article
Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units
2024
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Overview
Several materials and tissues are characterized by a microstructure composed of fibrous units embedded in a ground matrix. In this paper, a novel three-dimensional (3D) Fourier transform-based method for quantifying the distribution of fiber orientations is presented. The method allows for an accurate identification of individual fiber families, their in-plane and out-of-plane dispersion, and showed fast computation times. We validated the method using artificially generated 3D images, in terms of fiber dispersion by considering the error between the standard deviation of the reconstructed and the prescribed distributions of the artificial fibers. In addition, we considered the measured mean orientation angles of the fibers and validated the robustness using a measure of fiber density. Finally, the method is employed to reconstruct a full 3D view of the distribution of collagen fiber orientations based on in vitro second harmonic generation microscopy of collagen fibers in human and mouse skin. The dispersion parameters of the reconstructed fiber network can be used to inform mechanical models of soft fiber-reinforced materials and biological tissues that account for non-symmetrical fiber dispersion.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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