Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Miettinen, Arttu; Ojala, Antti; Wikström, Lisa; Joffe, Roberts; Madsen, Bo; Nättinen, Kalle; Kataja, M.

doi:10.1016/j.compositesa.2015.07.005

Cited by 17 publications

(12 citation statements)

References 29 publications

(34 reference statements)

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“…For each microvessel branch, the length L of the branch 42 , distance D between its end points, and the cross-sectional area A of the vessel was recorded. The cross-sectional area was measured by taking two-dimensional cross-sectional slices of the vessel and measuring its area from those 43 . The effective diameter of the vessel was then determined as = 2� ⁄ , tortuosity as / , and slenderness as / .…”

Section: Image Analysismentioning

confidence: 99%

Micrometer-resolution reconstruction and analysis of whole mouse brain vasculature by synchrotron-based phase-contrast tomographic microscopy

Miettinen

Zippo

Patera

et al. 2021

Preprint

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Nervous tissue metabolism is mainly supported by the dense thread of blood vessels which mainly provides fast supplies of oxygen and glucose. Recently, the supplying role of the brain vascular system has been examined in major neurological conditions such as the Alzheimer's and Parkinson's diseases. However, to date, fast and reliable methods for the fine level microstructural extraction of whole brain vascular systems are still unavailable. We present a methodological framework suitable for reconstruction of the whole mouse brain cerebral microvasculature by X-ray tomography with the unprecedented pixel size of 0.65 μm. Our measurements suggest that the resolving power of the technique is better than in many previous studies, and therefore it allows for a refinement of current measurements of blood vessel properties. Relevant insights emerged from analyses characterizing the regional morphology and topology of blood vessels. Specifically, vascular diameter and density appeared non-homogeneously distributed among the brain regions suggesting preferential sites for high-demanding metabolic requirements. Also, topological features such as the vessel branching points were non-uniformly distributed among the brain districts indicating that specific architectural schemes are required to serve the distinct functional specialization of the nervous tissue. In conclusion, here we propose a combination of experimental and computational method for efficient and fast investigations of the vascular system of entire organs with submicrometric precision.

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Section: Image Analysismentioning

confidence: 99%

Micrometer-resolution reconstruction and analysis of whole mouse brain vasculature by synchrotron-based phase-contrast tomographic microscopy

Miettinen

Zippo

Patera

et al. 2021

Preprint

Self Cite

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“…Some authors used the last method to compute either the local inertia matrices 26 or the structure tensor 27 . Miettinen et al 28 . also used the Gaussian convolution to compute the structure tensor from binarized images.…”

Section: Introductionmentioning

confidence: 99%

“…Some authors used the last method to compute either the local inertia matrices 26 or the structure tensor 27 . Miettinen et al 28 also used the Gaussian convolution to compute the structure tensor from bina-rized images. In each method resulting in a structure tensor or an inertia matrix, the local orientation can be evaluated by solving the eigenvalue problem.…”

Section: Introductionmentioning

confidence: 99%

Individual fibre separation in 3D fibrous materials imaged by X‐ray tomography

Depriester

Roscoat

Orgéas

et al. 2022

Journal of Microscopy

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Modelling the physical behaviour of fibrous materials still remains a great challenge because it requires to evaluate the inner structure of the different phases at the phase scale (fibre or matrix) and the at constituent scale (fibre). X-ray computed tomography (CT) imaging can help to characterize and to model these structures, since it allows separating the phases, based on the grey level of CT scans. However, once the fibrous phase has been isolated, automatically separating the fibres from each other is still very challenging. This work aims at proposing a method which allows separating the fibres and localizing the fibre-fibre contacts for various fibres geometries, that is: straight or woven fibres, with circular or non-circular cross sections, in a way that is independent of the fibres orientations. This method uses the local orientation of the structure formed by 220

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“…The smallest eigenvalue corresponds to the eigenvector pointing towards a direction of a primary orientation of the structures within this region. The approach is based on a computation of a structure tensor at every point of a medial axis of segmented fibers in reinforced composite, nonwoven fabrics, and fibrous porous networks, produced by a morphological thinning or trajectory tracing algorithm [25][26][27][28][29][30][31][32]. A similar approach was suggested for investigation of scaffold organization of the engineered heart valve tissue for post-and pre-implants [33].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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. Each acquired dataset of size 600x600x450 voxels was analyzed in less 2 minutes using standard PC equipped with a single GPU.

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Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

Cited by 17 publications

References 29 publications

Micrometer-resolution reconstruction and analysis of whole mouse brain vasculature by synchrotron-based phase-contrast tomographic microscopy

Micrometer-resolution reconstruction and analysis of whole mouse brain vasculature by synchrotron-based phase-contrast tomographic microscopy

Individual fibre separation in 3D fibrous materials imaged by X‐ray tomography

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

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