Potential of combined neutron and X-ray imaging to quantify local carbon contents in soil

Author(s):  
Genoveva Burca ◽  
Stephen Hillier ◽  
Pawala Ariyathilaka ◽  
Jumpei Fukumasu ◽  
Anke Herrmann ◽  
...  

<p>Soil organic carbon (SOC) is of key importance for soil functioning. It strongly impacts soil fertility, greenhouse gas emissions, nutrient retention, and contaminant degradation. The soil pore network determines how oxygen, water and nutrients are transported and exchanged in soil, and the architecture of the soil is therefore equally fundamental to soil functions. For a thorough understanding of the microbial habitat, the soil pore network architecture needs to be evaluated alongside with the spatial distribution of SOC, but the challenge ahead is the 3-D visualization of organic carbon at the micro-scale. At present, such visualizations are undertaken using staining agents, but their non-specific binding to other features in the soil aggravates evaluation of organic carbon at the micro-scale.</p><p>In the present study, we investigated the potential and limitations of using joint white-beam neutron and X-ray imaging for mapping the 3-dimensional organic carbon distribution in soil. This approach is viable because neutron and X-ray beams have complementary attenuation properties. Soil minerals consist to a large part of silicon and aluminium, elements which are relatively translucent to neutrons but attenuate X-rays. In contrast, attenuation of neutrons is strong for hydrogen, which is abundant in SOC, while hydrogen barely attenuates X-rays. When considering dried soil samples, the complementary attenuation for neutrons and X-rays may be used to quantify the fractions of air, SOC and minerals for any imaged voxel in a bi-modal 3-dimensional image, i.e. a combined neutron and X-ray image.</p><p>We collected neutron data at the IMAT beamline at the ISIS facility and X-ray data at the I12 beamline at the Diamond Light source, both located within the Rutherford Appleton Laboratory, Harwell, UK. The neutron image clearly showed variations in neutron attenuation within soil aggregates at approximately constant X-ray attenuations. This indicates a constant bulk density with varying organic matter and/or mineralogy. For samples with identical mineral composition, neutron attenuation data of sieved and repacked soil samples exhibited a large coefficient of determination (R<sup>2</sup>) in a regression between volumetric SOC content and neutron attenuation (0.9). Even larger R<sup>2</sup> (0.93) were obtained when the volumetric clay content was also included into the regression. However, when comparing soil samples with different mineralogy, R<sup>2</sup> dropped to 0.24 and 0.37, depending whether the clay content was considered or not. To improve the method, it is necessary to include specifics of the soil mineralogy. Here, analysing the time-of-flight neutron attenuation data collected at the IMAT beamline will provide further insights. In summary, our approach yielded promising results. We anticipate that quantitative 3-D imaging of organic carbon contents in soil will be possible in the near future.</p>

Author(s):  
M.G. Baldini ◽  
S. Morinaga ◽  
D. Minasian ◽  
R. Feder ◽  
D. Sayre ◽  
...  

Contact X-ray imaging is presently developing as an important imaging technique in cell biology. Our recent studies on human platelets have demonstrated that the cytoskeleton of these cells contains photondense structures which can preferentially be imaged by soft X-ray imaging. Our present research has dealt with platelet activation, i.e., the complex phenomena which precede platelet appregation and are associated with profound changes in platelet cytoskeleton. Human platelets suspended in plasma were used. Whole cell mounts were fixed and dehydrated, then exposed to a stationary source of soft X-rays as previously described. Developed replicas and respective grids were studied by scanning electron microscopy (SEM).


2021 ◽  
Vol 20 ◽  
pp. 153303382110101
Author(s):  
Thet-Thet Lwin ◽  
Akio Yoneyama ◽  
Hiroko Maruyama ◽  
Tohoru Takeda

Phase-contrast synchrotron-based X-ray imaging using an X-ray interferometer provides high sensitivity and high spatial resolution, and it has the ability to depict the fine morphological structures of biological soft tissues, including tumors. In this study, we quantitatively compared phase-contrast synchrotron-based X-ray computed tomography images and images of histopathological hematoxylin-eosin-stained sections of spontaneously occurring rat testicular tumors that contained different types of cells. The absolute densities measured on the phase-contrast synchrotron-based X-ray computed tomography images correlated well with the densities of the nuclear chromatin in the histological images, thereby demonstrating the ability of phase-contrast synchrotron-based X-ray imaging using an X-ray interferometer to reliably identify the characteristics of cancer cells within solid soft tissue tumors. In addition, 3-dimensional synchrotron-based phase-contrast X-ray computed tomography enables screening for different structures within tumors, such as solid, cystic, and fibrous tissues, and blood clots, from any direction and with a spatial resolution down to 26 μm. Thus, phase-contrast synchrotron-based X-ray imaging using an X-ray interferometer shows potential for being useful in preclinical cancer research by providing the ability to depict the characteristics of tumor cells and by offering 3-dimensional information capabilities.


2014 ◽  
Vol 68 (1) ◽  
pp. 66-72 ◽  
Author(s):  
Marco Stampanoni ◽  
Andreas Menzel ◽  
Ben Watts ◽  
Kevin S. Mader ◽  
Oliver Bunk
Keyword(s):  
X Ray ◽  

2021 ◽  
Author(s):  
Julius Muchui Thambura ◽  
Jeanette G.E du Plessis ◽  
Cheryl M E McCrindle ◽  
Tanita Cronje

Abstract Introduction Anecdotal evidence suggests that medical professionals in trauma units are requesting additional regional images using conventional x-ray systems, even after trauma patients have undergone full-body Lodox scans. Patients are then exposed to additional radiation, additional waiting times and an increased medical bill. This study aimed at investigating the extent to which Lodox systems were used in trauma units (n=28) in South Africa. Method In this descriptive cross-sectional study, the researcher invited one radiographer from the 28 hospitals in South Africa that use Lodox systems. Radiographers who were most experienced in using the Lodox system completed an online questionnaire. Results Twenty (71.43% n=20) out of twenty-eight radiographers responded. Most hospitals (90%, n=18) were referring patients for additional conventional x-ray images. Radiographers indicated that conventional x-rays were requested for the chest (27.80%, 10/36), the abdomen (16.67%, 6/36), the spine (13.89%, 5/36) and the extremities and skull (19.44%, 7/36). Additionally, radiographers reported using Lodox to perform procedures and examinations usually performed on conventional x-ray systems when conventional x-ray systems were not operational. Conclusion Currently, it is not clear if the use of conventional x-ray imaging following Lodox is necessary, but the results suggest that the practice is commonplace, with healthcare workers in most hospitals (90%, n=18) requesting additional x-ray imaging. The researcher thus recommends that an imaging protocol for Lodox imaging systems should be developed to guide the referral of the patients for further imaging.


Author(s):  
Dipayan Das ◽  
KC Santosh ◽  
Umapada Pal

Abstract Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in less than a couple of months, and the infection, caused by SARS-CoV-2, is spreading at an unprecedented rate. AI-driven tools are used to identify Coronavirus outbreaks as well as forecast their nature of spread, where imaging techniques are widely used, such as CT scans and chest X-rays (CXRs). In this paper, motivated by the fact that X-ray imaging systems are more prevalent and cheaper than CT scan systems, a deep learning-based Convolutional Neural Network (CNN) model, which we call Truncated Inception Net, is proposed to screen COVID-19 positive CXRs from other non-COVID and/or healthy cases. To validate our proposal, six different types of datasets were employed by taking the following CXRs: COVID-19 positive, Pneumonia positive, Tuberculosis positive, and healthy cases into account. The proposed model achieved an accuracy of 99.96% (AUC of 1.0) in classifying COVID- 19 positive cases from combined Pneumonia and healthy cases. Similarly, it achieved an accuracy of 99.92% (AUC of 0.99) in classifying COVID-19 positive cases from combined Pneumonia, Tuberculosis and healthy CXRs. To the best of our knowledge, as of now, the achieved results outperform the existing AI-driven tools for screening COVID-19 using CXRs.


2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
A. Teymurazyan ◽  
G. Pang

A Monte Carlo simulation was used to study imaging and dosimetric characteristics of a novel design of megavoltage (MV) X-ray detectors for radiotherapy applications. The new design uses Cerenkov effect to convert X-ray energy absorbed in optical fibres into light for MV X-ray imaging. The proposed detector consists of a matrix of optical fibres aligned with the incident X rays and coupled to an active matrix flat-panel imager (AMFPI) for image readout. Properties, such as modulation transfer function, detection quantum efficiency (DQE), and energy response of the detector, were investigated. It has been shown that the proposed detector can have a zero-frequency DQE more than an order of magnitude higher than that of current electronic portal imaging device (EPID) systems and yet a spatial resolution comparable to that of video-based EPIDs. The proposed detector is also less sensitive to scattered X rays from patients than current EPIDs.


2009 ◽  
Vol 13 (8) ◽  
pp. 1485-1502 ◽  
Author(s):  
L. W. de Jonge ◽  
P. Moldrup ◽  
P. Schjønning

Abstract. Soil functions and their impact on health, economy, and the environment are evident at the macro scale but determined at the micro scale, based on interactions between soil micro-architecture and the transport and transformation processes occurring in the soil infrastructure comprising pore and particle networks and at their interfaces. Soil structure formation and its resilience to disturbance are highly dynamic features affected by management (energy input), moisture (matric potential), and solids composition and complexation (organic matter and clay interactions). In this paper we review and put into perspective preliminary results of the newly started research program "Soil-it-is" on functional soil architecture. To identify and quantify biophysical constraints on soil structure changes and resilience, we claim that new approaches are needed to better interpret processes and parameters measured at the bulk soil scale and their links to the seemingly chaotic soil inner space behavior at the micro scale. As a first step, we revisit the soil matrix (solids phase) and pore system (water and air phases), constituting the complementary and interactive networks of soil infrastructure. For a field-pair with contrasting soil management, we suggest new ways of data analysis on measured soil-gas transport parameters at different moisture conditions to evaluate controls of soil matrix and pore network formation. Results imply that some soils form sponge-like pore networks (mostly healthy soils in terms of agricultural and environmental functions), while other soils form pipe-like structures (agriculturally poorly functioning soils), with the difference related to both complexation of organic matter and degradation of soil structure. The recently presented Dexter et al. (2008) threshold (ratio of clay to organic carbon of 10 kg kg−1) is found to be a promising constraint for a soil's ability to maintain or regenerate functional structure. Next, we show the Dexter et al. (2008) threshold may also apply to hydrological and physical-chemical interface phenomena including soil-water repellency and sorption of volatile organic vapors (gas-water-solids interfaces) as well as polycyclic aromatic hydrocarbons (water-solids interfaces). However, data for differently-managed soils imply that energy input, soil-moisture status, and vegetation (quality of eluded organic matter) may be equally important constraints together with the complexation and degradation of organic carbon in deciding functional soil architecture and interface processes. Finally, we envision a road map to soil inner space where we search for the main controls of particle and pore network changes and structure build-up and resilience at each crossroad of biophysical parameters, where, for example, complexation between organic matter and clay, and moisture-induced changes from hydrophilic to hydrophobic surface conditions can play a role. We hypothesize that each crossroad (e.g. between organic carbon/clay ratio and matric potential) may control how soil self-organization will manifest itself at a given time as affected by gradients in energy and moisture from soil use and climate. The road map may serve as inspiration for renewed and multi-disciplinary focus on functional soil architecture.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Pasquale Delogu ◽  
Vittorio Di Trapani ◽  
Luca Brombal ◽  
Giovanni Mettivier ◽  
Angelo Taibi ◽  
...  

Abstract The limits of mammography have led to an increasing interest on possible alternatives such as the breast Computed Tomography (bCT). The common goal of all X-ray imaging techniques is to achieve the optimal contrast resolution, measured through the Contrast to Noise Ratio (CNR), while minimizing the radiological risks, quantified by the dose. Both dose and CNR depend on the energy and the intensity of the X-rays employed for the specific imaging technique. Some attempts to determine an optimal energy for bCT have suggested the range 22 keV–34 keV, some others instead suggested the range 50 keV–60 keV depending on the parameters considered in the study. Recent experimental works, based on the use of monochromatic radiation and breast specimens, show that energies around 32 keV give better image quality respect to setups based on higher energies. In this paper we report a systematic study aiming at defining the range of energies that maximizes the CNR at fixed dose in bCT. The study evaluates several compositions and diameters of the breast and includes various reconstruction algorithms as well as different dose levels. The results show that a good compromise between CNR and dose is obtained using energies around 28 keV.


2017 ◽  
Vol 33 (5) ◽  
pp. 721-728 ◽  
Author(s):  
Zephania R. Odek ◽  
Bhagwati Prakash ◽  
Terry J. Siebenmorgen

Abstract. X-ray imaging is a viable method of fissure detection in rough rice kernels owing to the ability of X-rays to penetrate hulls, thus allowing visualization of internal rice kernel structure. Traditional methods of fissure detection are only applicable for brown and milled rice, and therefore cannot be used to study fissures developed during rough rice drying. In this study, the fissure detection capability of an X-ray system was evaluated and the relationship between head rice yield (HRY), as measured through laboratory milling, and the percentage of fissured rough rice kernels was determined. Long-grain rice lots of various cultivars were dried using heated air at 60°C, 10% relative humidity (RH) for five drying durations to produce different degrees of fissuring, and then milled to determine HRY. A strong linear correlation (R2 = 0.95) between HRY and the percentage of fissured rough rice kernels after drying was determined. This correlation confirms the substantial impact that kernel fissures have on milling yields. Overall, these findings show the effectiveness of X-ray imaging in rough rice fissure detection, which could allow for drying research that may provide a better understanding of kernel fissuring kinetics. Keywords: Fissures, Grainscope, Head rice yield, Rice drying, X-ray imaging.


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