scholarly journals Machine learning denoising of high-resolution X-ray nanotomography data

2022 ◽  
Vol 29 (1) ◽  
Author(s):  
Silja Flenner ◽  
Stefan Bruns ◽  
Elena Longo ◽  
Andrew J. Parnell ◽  
Kilian E. Stockhausen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quantitative Analysis ◽  
High Resolution ◽  
Median Filter ◽  
Automatic Segmentation ◽  
Structural Features ◽  
Nonlocal Means ◽  
X Ray ◽  
Research Areas ◽  
Wide Range

High-resolution X-ray nanotomography is a quantitative tool for investigating specimens from a wide range of research areas. However, the quality of the reconstructed tomogram is often obscured by noise and therefore not suitable for automatic segmentation. Filtering methods are often required for a detailed quantitative analysis. However, most filters induce blurring in the reconstructed tomograms. Here, machine learning (ML) techniques offer a powerful alternative to conventional filtering methods. In this article, we verify that a self-supervised denoising ML technique can be used in a very efficient way for eliminating noise from nanotomography data. The technique presented is applied to high-resolution nanotomography data and compared to conventional filters, such as a median filter and a nonlocal means filter, optimized for tomographic data sets. The ML approach proves to be a very powerful tool that outperforms conventional filters by eliminating noise without blurring relevant structural features, thus enabling efficient quantitative analysis in different scientific fields.

scholarly journals Shadow monochromatic backlighting: Large-field high resolution X-ray shadowgraphy with improved spectral tunability

2001 ◽  
Vol 19 (2) ◽  
pp. 285-293 ◽  
Author(s):  
T.A. PIKUZ ◽  
A. YA. FAENOV ◽  
M. FRAENKEL ◽  
A. ZIGLER ◽  
F. FLORA ◽  
...  
Keyword(s):  
High Resolution ◽  
High Spatial Resolution ◽  
Field Of View ◽  
Large Field ◽  
X Ray ◽  
Traditional Scheme ◽  
Wide Range ◽  
Wide Wavelength Range ◽  
Bent Crystals ◽  
First Time

The shadow monochromatic backlighting (SMB) scheme, a modification of the well-known soft X-ray monochromatic backlighting scheme, is proposed. It is based on a spherical crystal as the dispersive element and extends the traditional scheme by allowing one to work with a wide range of Bragg angles and thus in a wide spectral range. The advantages of the new scheme are demonstrated experimentally and supported numerically by ray-tracing simulations. In the experiments, the X-ray backlighter source is a laser-produced plasma, created by the interaction of an ultrashort pulse, Ti:Sapphire laser (120 fs, 3–5 mJ, 1016 W/cm2 on target) or a short wavelength XeCl laser (10 ns, 1–2 J, 1013 W/cm2 on target) with various solid targets (Dy, Ni + Cr, BaF2). In both experiments, the X-ray sources are well localized spatially (∼20 μm) and are spectrally tunable in a relatively wide wavelength range (λ = 8–15 Å). High quality monochromatic (δλ/λ ∼ 10−5–10−3) images with high spatial resolution (up to ∼4 μm) over a large field of view (a few square millimeters) were obtained. Utilization of spherically bent crystals to obtain high-resolution, large field, monochromatic images in a wide range of Bragg angles (35° < Θ < 90°) is demonstrated for the first time.

Quantitative analysis of the quantum dot superlattice by high-resolution x-ray diffraction

2013 ◽  
Vol 113 (16) ◽  
pp. 163506 ◽  
Author(s):  
N. N. Faleev ◽  
C. Honsberg ◽  
V. I. Punegov
Keyword(s):  
Quantitative Analysis ◽  
High Resolution ◽  
Quantum Dot ◽  
X Ray Diffraction ◽  
X Ray

scholarly journals Measurement of three-dimensional displacement field in piled embankments using synchrotron X-ray tomography

2019 ◽  
Vol 56 (6) ◽  
pp. 885-892 ◽  
Author(s):  
Louis King ◽  
Abdelmalek Bouazza ◽  
Anton Maksimenko ◽  
Will P. Gates ◽  
Stephen Dubsky
Keyword(s):  
High Resolution ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Physical Models ◽  
Scale Model ◽  
Small Scale ◽  
Full Field ◽  
X Ray ◽  
Wide Range ◽  
Piled Embankments

The measurement of displacement fields by nondestructive imaging techniques opens up the potential to study the pre-failure mechanisms of a wide range of geotechnical problems within physical models. With the advancement of imaging technologies, it has become possible to achieve high-resolution three-dimensional computed tomography volumes of relatively large samples, which may have previously resulted in excessively long scan times or significant imaging artefacts. Imaging of small-scale model piled embankments (142 mm diameter) comprising sand was undertaken using the imaging and medical beamline at the Australian Synchrotron. The monochromatic X-ray beam produced high-resolution reconstructed volumes with a fine texture due to the size and mineralogy of the sand grains as well as the phase contrast enhancement achieved by the monochromatic X-ray beam. The reconstructed volumes were well suited to the application of digital volume correlation, which utilizes cross-correlation techniques to estimate three-dimensional full-field displacement vectors. The output provides insight into the strain localizations that develop within piled embankments and an example of how advanced imaging techniques can be utilized to study the kinematics of physical models.

scholarly journals Employing Texture Features of Chest X-Ray Images and Machine Learning in COVID-19 Detection and Classification

MENDEL ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 9-17
Author(s):  
Hiam Alquran ◽  
Mohammad Alsleti ◽  
Roaa Alsharif ◽  
Isam Abu Qasmieh ◽  
Ali Mohammad Alqudah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Texture Features ◽  
Automated System ◽  
Rt Pcr ◽  
False Negatives ◽  
X Ray ◽  
Organ Systems ◽  
Wide Range ◽  
Chest X Ray

The novel coronavirus (nCoV-19) was first detected in December 2019. It had spread worldwide and was declared coronavirus disease (COVID-19) pandemic by March 2020. Patients presented with a wide range of symptoms affecting multiple organ systems predominantly the lungs. Severe cases required intensive care unit (ICU) admissions while there were asymptomatic cases as well. Although early detection of the COVID-19 virus by Real-time reverse transcription-polymerase chain reaction (RT-PCR) is effective, it is not efficient; as there can be false negatives, it is time consuming and expensive. To increase the accuracy of in-vivo detection, radiological image-based methods like a simple chest X-ray (CXR) can be utilized. This reduces the false negatives as compared to solely using the RT-PCR technique. This paper employs various image processing techniques besides extracted texture features from the radiological images and feeds them to different artificial intelligence (AI) scenarios to distinguish between normal, pneumonia, and COVID-19 cases. The best scenario is then adopted to build an automated system that can segment the chest region from the acquired image, enhance the segmented region then extract the texture features, and finally, classify it into one of the three classes. The best overall accuracy achieved is 93.1% by exploiting Ensemble classifier. Utilizing radiological data to conform to a machine learning format reduces the detection time and increase the chances of survival.

“Standardless” Quantitative Analysis by Electron-Excited Energy Dispersive X-Ray Spectrometry: What is its Proper Role?

1998 ◽  
Vol 4 (S2) ◽  
pp. 194-195
Author(s):  
Dale E. Newbury
Keyword(s):  
Quantitative Analysis ◽  
Energy Dispersive ◽  
K Value ◽  
X Ray ◽  
Electron Probe Microanalyzer ◽  
Proper Role ◽  
Wide Range ◽  
Measured Characteristic ◽  
Electron Range

The development of energy dispersive x-ray spectrometry (EDS) has had a profound impact on the methodology of quantitative x-ray microanalysis of thick specimens (i.e., thickness≫ electron range) as performed in electron beam instruments. By equipping the scanning electron microscope (SEM) with EDS, quantitative x-ray microanalysis has become commonly available to a wide range of users, at least some of whom have only a modest background in analytical science. An important aspect of the development of quantitative analysis by EDS has been the extensive analytical experience gained during the development of the electron probe microanalyzer (EPMA) equipped with wavelength dispersive x-ray spectrometers (WDS). The critical measurement step for quantitative WDS analysis was recognized to be the determination of the “k-value”:k = Iunk / Istd (1)where I is the measured characteristic intensity of a specific x-ray peak, corrected for background and peak overlaps, for both the unknown and the standard.

High Resolution EM Study of Wüstite

1974 ◽  
Vol 32 ◽  
pp. 352-353 ◽  
Author(s):  
Sumio Iijima
Keyword(s):  
High Resolution ◽  
Diffraction Method ◽  
X Ray Diffraction ◽  
Repeat Distance ◽  
X Ray ◽  
Integral Number ◽  
Deviation From Stoichiometry ◽  
Wide Range ◽  
Cation Sites ◽  
Range Of Variation

Wüstite (Fe1-x0) has recieved considerable attention because of a wide range of variation in x. The deviation from stoichiometry is known to be due to vacancies on cation sites. Koch and Cohen, having studied this material in detail using an X-ray diffraction method, concluded that the defects present in Fe1-x0 are clusters of 13 octahedral vacancies and 4 tetrahedral ions. These clusters are arranged periodically but the repeat distance in the [100] direction is not an integral number of structures of the basic NaCl-type. The observed spacing of superstructure peaks may correspond to the average repeat distance.

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