scholarly journals A modular U-Net for automated segmentation of X-ray tomography images in composite materials

2021 ◽  
Author(s):  
João Paulo Casagrande Bertoldo ◽  
Etienne Decencière Ferrandière ◽  
David Ryckelynck ◽  
Henry Proudhon
Keyword(s):  
Polyamide 66 ◽  
Promising Alternative ◽  
High Resolution Data ◽  
X Ray ◽  
3D Tomography ◽  
Glass Fiber Reinforced ◽  
Segmentation Methods ◽  
Model Finding ◽  
X Ray Computed ◽  
2D And 3D

Abstract X-ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome, demanding automated data pipelines capable of dealing with non-trivial 3D images. Deep learning has demonstrated success in many image processing tasks, including material science applications, showing a promising alternative for a human-free segmentation pipeline. In this paper a modular interpretation of U-Net (Modular U-Net) is proposed and trained to segment 3D tomography images of a three-phased glass fiber-reinforced Polyamide 66. We compare 2D and 3D versions of our model, finding that the former is slightly better than the latter. We observe that human-comparable results can be achievied even with only 10 annotated layers and using a shallow U-Net yields better results than a deeper one. As a consequence, Neural Network (NN) show indeed a promising venue to automate XCT data processing pipelines needing no human, adhoc intervention.

scholarly journals A Modular U-Net for Automated Segmentation of X-Ray Tomography Images in Composite Materials

2021 ◽  
Vol 8 ◽  
Author(s):  
João P. C. Bertoldo ◽  
Etienne Decencière ◽  
David Ryckelynck ◽  
Henry Proudhon
Keyword(s):  
Materials Science ◽  
Polyamide 66 ◽  
Promising Alternative ◽  
High Resolution Data ◽  
X Ray ◽  
3D Tomography ◽  
Glass Fiber Reinforced ◽  
Segmentation Methods ◽  
Model Finding ◽  
X Ray Computed

X-Ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome, demanding automated data pipelines capable of dealing with non-trivial 3D images. Meanwhile, deep learning has demonstrated success in many image processing tasks, including materials science applications, showing a promising alternative for a human-free segmentation pipeline. However, the rapidly increasing number of available architectures can be a serious drag to the wide adoption of this type of models by the end user. In this paper a modular interpretation of U-Net (Modular U-Net) is proposed with a parametrized architecture that can be easily tuned to optimize it. As an example, the model is trained to segment 3D tomography images of a three-phased glass fiber-reinforced Polyamide 66. We compare 2D and 3D versions of our model, finding that the former is slightly better than the latter. We observe that human-comparable results can be achievied even with only 13 annotated slices and using a shallow U-Net yields better results than a deeper one. As a consequence, neural networks show indeed a promising venue to automate XCT data processing pipelines needing no human, adhoc intervention.

scholarly journals Gold Exploration in Two and Three Dimensions: Improved and Correlative Insights from Microscopy and X-Ray Computed Tomography

Minerals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 476
Author(s):  
Joshua Chisambi ◽  
Bjorn von der Heyden ◽  
Muofhe Tshibalanganda ◽  
Stephan Le Roux
Keyword(s):  
Computed Tomography ◽  
Spatial Distribution ◽  
Gold Mineralization ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Low Grade ◽  
X Ray ◽  
3D Space ◽  
X Ray Computed ◽  
2D And 3D

In this contribution, we highlight a correlative approach in which three-dimensional structural/positional data are combined with two dimensional chemical and mineralogical data to understand a complex orogenic gold mineralization system; we use the Kirk Range (southern Malawi) as a case study. Three dimensional structures and semi-quantitative mineral distributions were evaluated using X-ray Computed Tomography (XCT) and this was augmented with textural, mineralogical and chemical imaging using Scanning Electron Microscopy (SEM) and optical microscopy as well as fire assay. Our results detail the utility of the correlative approach both for quantifying gold concentrations in core samples (which is often nuggety and may thus be misrepresented by quarter- or half-core assays), and for understanding the spatial distribution of gold and associated structures and microstructures in 3D space. This approach overlays complementary datasets from 2D and 3D analytical protocols, thereby allowing a better and more comprehensive understanding on the distribution and structures controlling gold mineralization. Combining 3D XCT analyses with conventional 2D microscopies derive the full value out of a given exploration drilling program and it provides an excellent tool for understanding gold mineralization. Understanding the spatial distribution of gold and associated structures and microstructures in 3D space holds vast potential for exploration practitioners, especially if the correlative approach can be automated and if the resultant spatially-constrained microstructural information can be fed directly into commercially available geological modelling software. The extra layers of information provided by using correlative 2D and 3D microscopies offer an exciting new tool to enhance and optimize mineral exploration workflows, given that modern exploration efforts are targeting increasingly complex and low-grade ore deposits.

scholarly journals Computed microtomography in the analysis of fiber migration in yarn

2013 ◽  
Vol 13 (1) ◽  
pp. 28-32 ◽  
Author(s):  
Marta Toda ◽  
Katarzyna Ewa Grabowska
Keyword(s):  
Cross Sections ◽  
Two Dimensional ◽  
X Ray ◽  
Testing Method ◽  
Computed Microtomography ◽  
X Ray Computed ◽  
Nondestructive Testing Method ◽  
2D And 3D ◽  
Migration Testing ◽  
Non Destructive

Abstract This study is a short analysis of the use of computer microphotography in fiber migration testing as a modern nondestructive testing method. Microtomography operates similarly to X-ray computed tomography systems used in medicine, but with much better resolution owing to the use of a smaller radiation spot. The internal structure is reconstructed as a series of two-dimensional cross-sections that are then used to create 2D and 3D morphological objects. This process is non-destructive and does not require special preparation of a testing material.

scholarly journals Microstructure-mechanical properties relationships in vibration welded glass-fiber-reinforced polyamide 66: A high-resolution X-ray microtomography study

2020 ◽  
Vol 85 ◽  
pp. 106454 ◽  
Author(s):  
Eeva Mofakhami ◽  
Sylvie Tencé-Girault ◽  
Jonathan Perrin ◽  
Mario Scheel ◽  
Laurent Gervat ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
High Resolution ◽  
Glass Fiber ◽  
Fiber Reinforced ◽  
Polyamide 66 ◽  
X Ray ◽  
Glass Fiber Reinforced

Addressing Failure Analysis Challenges in Advanced Packages and MEMS using a Novel Phase and Darkfield X-Ray Imaging System

2020 ◽  
Author(s):  
S.H. Lau ◽  
Sheraz Gul ◽  
Guibin Zan ◽  
David Vine ◽  
Sylvia Lewis ◽  
...  
Keyword(s):  
Failure Modes ◽  
Imaging System ◽  
Dark Field ◽  
Organic Substrates ◽  
Mechanical Shock ◽  
X Ray ◽  
X Ray Imaging ◽  
X Ray Computed ◽  
2D And 3D ◽  
Non Destructive

Abstract Currently gaps in non-destructive 2D and 3D imaging in PFA for advanced packages and MEMS exist due to lack of resolution to resolve sub-micron defects and the lack of contrast to image defects within the low Z materials. These low Z defects in advanced packages include sidewall delamination between Si die and underfill, bulk cracks in the underfill, in organic substrates, Redistribution Layer, RDL; Si die cracks; voids within the underfill and in the epoxy. Similarly, failure modes in MEMS are often within low Z materials, such as Si and polymers. Many of these are a result of mechanical shock resulting in cracks in structures, packaging fractures, die adhesion issues or particles movements into critical locations. Most of these categories of defects cannot be detected non-destructively by existing techniques such as C-SAM or microCT (micro x-ray computed tomography) and XRM (X-ray microscope). We describe a novel lab-based X-ray Phase contrast and Dark-field/Scattering Contrast system with the potential to resolve these types of defects. This novel X-ray microscopy has spatial resolution of 0.5 um in absorption contrast and with the added capability of Talbot interferometry to resolve failure issues which are related to defects within organic and low Z components.

scholarly journals On the enigma of Palaenigma wrangeli (Schmidt), a conulariid with a partly non-mineralized skeleton

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12374
Author(s):  
Björn Kröger ◽  
Olev Vinn ◽  
Ursula Toom ◽  
Ian J. Corfe ◽  
Jukka Kuva ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Soft Bottom ◽  
Upper Ordovician ◽  
Baltic Basin ◽  
X Ray ◽  
X Ray Computed ◽  
3D Scans ◽  
2D And 3D ◽  
Eastern Baltic ◽  
Scanning Electron

Palaenigma wrangeli (Schmidt) is a finger-sized fossil with a tetraradiate conical skeleton; it occurs as a rare component in fossiliferous Upper Ordovician strata of the eastern Baltic Basin and is known exclusively from north Estonia. The systematic affinities and palaeoecology of P. wrangeli remained questionable. Here, the available specimens of P. wrangeli have been reexamined using scanning electron microscopy and x-ray computed tomography (microCT). Additionally, the elemental composition of the skeletal elements has been checked using energy dispersive X-ray spectroscopy. The resulting 2D-, and 3D-scans reveal that P. wrangeli consists of an alternation of distinct calcium phosphate (apatite) lamellae and originally organic-rich inter-layers. The lamellae form four semicircular marginal pillars, which are connected by irregularly spaced transverse diaphragms. Marginally, the diaphragms and pillar lamellae are not connected to each other and thus do not form a closed periderm structure. A non-mineralized or poorly mineralized external periderm existed originally in P. wrangeli but is only rarely and fragmentary preserved. P. wrangeli often co-occurs with conulariids in fossil-rich limestone with mudstone–wackestone lithologies. Based on the new data, P. wrangeli can be best interpreted as a poorly mineralized conulariinid from an original soft bottom habitat. Here the new conulariinid family Palaenigmaidae fam. nov. is proposed as the monotypic taxon for P. wrangeli.

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