Dual-energy X-ray Radiography Research Articles

Inspection of cargo using dual-energy X-ray radiography: A review

Cargo inspection is essential for material discrimination and security aims such as threat detection/identification. In this paper, dual-energy X-ray imaging for cargo inspection is studied. Dual-energy imaging challenges such as improving image quality (i.e. noise reduction), automatically removing image defects and errors, and developing algorithms for image detection and identification are investigated. Selecting the right method for image formation, selecting the right source, choosing appropriate X-ray energies, and the appropriate detectors are also discussed. Cargo inspection using dual-energy X-ray shows that not many techniques have been presented for denoising, and there is no comparative comparison between them. Material discrimination using dual-energy X-ray has had significant success in cargo, especially when convolutional neural network (CNN) is integrated with traditional techniques. However, it will have limitations on performance due to the existence of challenges such as the need for large data and the possibility of noise presence in the extracted features. It seems that future studies should cover these issues.

Investigating four algorithms for material discrimination in a simulated dual-energy radiography system

In the present work, a dual-energy X-ray radiography system was simulated using MCNPX code. Then, material discrimination curves for graphite, aluminum, steel, and lead materials were obtained using four algorithms, including log-log, R-T, r-θ, and α1-α2. The results show that R-T, r-θ, and α1-α2 algorithms have better performance. Also, due to the less overlap of material discrimination curves for low sample thicknesses, the R-T algorithm can be a better choice for obtaining material discrimination curves in dual-energy radiography systems.

Developing a new approach for material discrimination using modular radial basis neural networks based on dual-energy X-ray radiography

Challenges, especially, identification of correlation of attenuation coefficients at high/low energy X-ray, stochastic noise on images, source energy fluctuation, and angular drop-off of X-ray energy/dose rate affect the quality of the material discrimination using dual-energy X-ray radiography. In this study, a new approach using radial basis network (RBN) is applied for the identification of materials. A modular structure, in which each module is responsible for the identification of a single material-thickness is developed. Each module with its specific RBN not only is trained to identify its own material-thickness but also is trained to reject the other ones. The activation/radial function of each network is with standard deviation proportional to the distribution of a specific material-thickness transparency. This technique tries to handle the effects of the mentioned challenges which have quasi-radial distribution on the constructed image. Moreover, the cross-correlation between attenuation coefficients at high/low energy X-ray is detected by the neural network. The results show an acceptable performance of the proposed approach. The noticeable advantages are: 1- Instead of utilizing qualitative discrimination techniques such as pseudo-colouring, the materials are discriminated quantitatively which is more important when the number of material- thicknesses is increased. 2- The modular structure makes it possible to add new material- thickness without unfavourably affecting the existing networks (i.e., there is no need to retrain them). 3- The exact percentage of correct identification, incorrect identification, and misidentification are given 4- Bipolar representation makes possible to identify material-thickness without need/with less need to human operators 5- Material discrimination may be done by a more straightforward computational tool because classical machine learning is applied instead of deep learning.

Inverse Method for Noninvasive Material Discrimination with Multienergy X-Ray Radiography

Active x-ray inspections have great potential for noninvasive detection of illicit materials. Dual-energy x-ray radiography, in particular, has been used to determine material composition by utilizing the energy-dependence of the x-ray attenuation coefficients. However, current implementations of this method are limited in their ability to determine the material composition of composite objects. Here we present an inverse algorithm that uses multienergy x-ray radiography data to noninvasively reconstruct the contents of a container. A critical feature of the current contribution is that material identification can be performed using conventional detectors and x-ray spectra with different endpoint energies produced by varying nothing more than the tube voltage. Adaptive regularization is used to increase the accuracy of material estimations from multienergy data sets. The utility of these methods is demonstrated with experimentally acquired radiographs obtained using a tunable x-ray source that produces spectra with endpoint energies of 100--450 keV. The object inspected is a scale model of a nuclear materials storage container composed of three-dimensional printed plastic and stainless-steel spheres inside a thin-walled steel container. Reconstructions of the steel sphere thicknesses are within a root-mean-square error of 0.37 cm.

Position-Sensitive Bulk and Surface Element Analysis of Decorated Porcelain Artifacts.

Non-destructive characterization of decorated porcelain artifacts requires the joint use of surface-analytical methods for the decorative surface pattern and methods of high penetration depth for bulk-representative chemical composition. In this research, we used position-sensitive X-ray Fluorescence Spectrometry (XRF) and Prompt-gamma activation analysis (PGAA) for these purposes, assisted by 3D structured-light optical scanning and dual-energy X-ray radiography. The proper combination of the near-surface and bulk element composition data can shed light on raw material use and manufacturing technology of ceramics.

Inspection of Cargo Using Dual-Energy X-Ray Radiography: A Review

Inspection of Cargo Using Dual-Energy X-Ray Radiography: A Review

Studying the effect of the scanned objects’ location on material discrimination in a dual-energy cargo inspection system

Dual-energy X-ray radiography is an important inspection technology in imaging large cargos for finding illegal materials. A useful aspect of dual-energy X-ray radiography is the possibility of discriminating and identifying materials with different atomic numbers which can be obtained by imaging large cargos at two different X-ray energies (normally above 3 MeV). The performance of both single and dual-energy radiography depends on many factors such as beam energy and filtration, radiation dose, scanned object size, the content of the object, etc. One of the parameters that can affect the quality of the material discrimination is the location of the scanned objects (different heights from the ground). It is due to the fact that the generated X-ray beams from the Linac are angle dependent and therefore, energy spectrums vary at different angles. In this work, our main goal was to find equations for material discrimination curves as a function of height for graphite, aluminum, steel, and lead materials. After obtaining simulated and experimental curves for a range of heights, we searched for best-fitting polynomial equations and finally the best equation for each material was obtained. Our results showed that there is a good agreement between the simulated and experimental curves compared to those obtained from the fitted equations. According to obtained results, material discrimination curves can be obtained for a range of heights using the fitted equations without performing any further simulation and experimental processes. This can be very helpful in reducing calibration time and increasing calibration accuracy in inspection systems.

Classification-based material decomposition method for photon counting-based spectral radiography: Application to plastic sorting

Dual-energy X-ray radiography has been commonly used for materials separation. However, its performance is limited, especially for the separation of close materials or the identification of multiple materials. To cope with this problem, we propose to investigate the material decomposition ability of spectral radiography based on photon-counting detector. The latter having energy resolving capability can provide spectral information of several energy bins and thus enables selective imaging of multiple materials. In this framework, a classification-based patchwise regularized decomposition method was proposed to gain better differentiation between materials. It consists of performing several decompositions with reduced number of materials in the basis and classifying these decompositions using their cost function values. The results on simulations showed that, in the presence of Poisson noise, the method without classification can separate acrylonitrile-butadiene-styrene (ABS) from three kinds of flame retardants (FRs: brominated FR, chlorinated FR and phosphorus FR), but that the type of FR cannot be identified. With the classification technique, ABS and three kinds of FRs can be both separated and identified at the same time when the thickness was as large as 2 mm or 4 mm. The results on real data from physical photon-counting detector further confirm that the ABS, Br and Cl can be separated from each other.

Compact four-layer Timepix-based particle tracker WidePIX 3D: the first applications in X-ray CT imaging

WidePIX 3D is a compact Timepix-based particle tracking detector with 3D position sensitivity. The device consists of four Timepix chips with 300 μm silicon sensors tightly stacked together. The sensor volume is, therefore, divided into a 3D array of 256 × 256 × 4 voxels. Dual-energy X-ray imaging with sandwich detector is already known as single-shot dual-energy X-ray radiography utilizing a two-layer detector. In the case of WidePIX 3D, the detector can provide up to four sample images produced by different photon spectra from a single exposure. Furthermore, the detection threshold of each layer can be individually adjusted to optimize the resolving performance for elements expected within the scanned sample. In this contribution we present the first results of using the WidePIX 3D detector as an imaging camera for multi-channel energy-sensitive X-ray CT. The procedure of precise threshold-energy calibration of the detector using characteristic X-ray lines will be described and material-resolving CT data will be demonstrated.

A dynamic material discrimination algorithm for dual MV energy X-ray digital radiography

Dual-energy X-ray radiography has become a well-established technique in medical, industrial, and security applications, because of its material or tissue discrimination capability. The main difficulty of this technique is dealing with the materials overlapping problem. When there are two or more materials along the X-ray beam path, its material discrimination performance will be affected. In order to solve this problem, a new dynamic material discrimination algorithm is proposed for dual-energy X-ray digital radiography, which can also be extended to multi-energy X-ray situations. The algorithm has three steps: α-curve-based pre-classification, decomposition of overlapped materials, and the final material recognition. The key of the algorithm is to establish a dual-energy radiograph database of both pure basis materials and pair combinations of them. After the pre-classification results, original dual-energy projections of overlapped materials can be dynamically decomposed into two sets of dual-energy radiographs of each pure material by the algorithm. Thus, more accurate discrimination results can be provided even with the existence of the overlapping problem. Both numerical and experimental results that prove the validity and effectiveness of the algorithm are presented.

X-ray and neutron interrogation of air cargo for mobile applications

A system for scanning break-bulk cargo for mobile applications is presented. This combines a 140kV multi-view, multi-energy X-ray system with 2.5MeV neutrons. The system uses dual energy X-ray radiography with neutron radiography. The X-ray and neutron systems were designed to be collocated in a mobile environment. Various materials were interrogated with the intent of distinguishing threat materials such as explosives from similar benign materials. In particular, the identification of threats and bengins with nearly identical effective atomic numbers has been demonstrated.

Bone mineral density assessed by dual energy X-ray radiography in patients with alcoholic or HBV-related liver cirrhosis

Objective To investigate the differences of bone mineral density( BMD) among the patients with alcoholic or HBV-related liver cirrhosis,and healthy controls. Methods Dual-energy X-ray radiography was employed to determine the BMD of he lumbar vertebra and bilateral hip joints in 57 patients with alcoholic cirrhosis,67 with hepatitis B cirrhosis,and 175 healthy controls. The demographic data and clinical characteristics( hepatic fibrosis and hepatic function) of all the participants were collected. Independent sample t-test was used to compare the differences among 3 groups and multiple classified logistical regression analysis was used to evaluate factors influencing BMD. Results The BMD of alcoholic cirrhosis and HBV-related cirrhosis patients were significantly lower than that of healthy controls( P 0. 01),and the BMD in alcohol cirrhosis patients was significantly lower than that in HBV-related cirrhosis patients( P 0. 05). Univariate logistic regression analysis identified that female gender,elder age,liver cirrhosis degree,and liver function were significantly correlated with the levels of BMD( P 0. 01). Multivariate analysis showed that alcoholic cirrhosis( OR = 2. 053,95% CI = 1. 931-3. 852) and HBV-related cirrhosis( OR = 1. 521,95% CI = 1. 342-2. 354) were the independent risks of reduced BMD in patients. Conclusion BMD levels of patients with alcoholic cirrhosis and HBV-related cirrhosis are significantly lower than that of the healthy controls,and hepatic cirrhosis is independent factor of osteoporosis.

Dual-energy X-ray radiography for automatic high-Z material detection

There is an urgent need for high-Z material detection in cargo. Materials with Z>74 can indicate the presence of fissile materials or radiation shielding. Dual (high) energy X-ray material discrimination is based on the fact that different materials have different energy dependence in X-ray attenuation coefficients. This paper introduces the basic physics and analyzes the factors that affect dual-energy material discrimination performance. A detection algorithm is also discussed.

Grade of fine composite mineral particles by dual-energy X-ray radiography

Standard X-ray radiographs of a composite particle made up by two mineralogical species with different linear attenuation coefficients produce 2D attenuation images that do not allow differentiating between a thin high stopping power and a thick low stopping power-mineralogical inclusion. Dual-energy (DE) imaging—i.e., a pair of radiographs taken at different incident X-ray energy—followed by digital image subtraction allows transforming the log processed energy images into two thickness images. This linear transformation permits the estimation of the particle volumetric content in the two phases and it is fast, as required for the development of an online ‘mineral liberation’ or a ‘washability’ sensor or a ‘valuable-phase-inclusion’ detector. In this paper, micro-CT was used to reconstruct fine particle slices so that the thickness of the two phases could be precisely calculated and compared with that one derived by DE. Preliminary experiments with monochromatic X-ray demonstrated the potential of the DE method to retrieve the particle grade. The tests were conducted with fine composite particles made up of two mineralogical species. Due to the nonhomogeneous composition and density variation within the two mineralogical phases segmented and also to partial volume effects in the tomographic reconstruction of particle slices, each of the two segmented phases have a Gaussian distribution of the linear attenuation coefficient μ (rather that one single value) and values of the σ( μ) such that the density distribution right tail of the species with the lower μ overlaps the left tail of the other species giving rise to a bimodal distribution of μ within the particle. This material feature adds further complexity to the problem.