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In this paper, based on an invited talk at SORMA (May 2016), we present an overview of x-ray sources, detectors and system configurations for non-intrusive inspection (NII) of cargo containers. Our emphasis is on dual-energy x-ray NII for detecting high-atomic-number ( $\text {Z}\geq 72$ ) materials such as tungsten shielding and special nuclear materials (SNM). Standard single-energy (MeV and above) x-rays needed to penetrate and image cargo provide little SNM contrast, whereas dual-energy x-ray NII is demonstrated as a way to improve the selectivity of materials with Z $\text {Z}\geq 72$ . For two possible dual-energy x-ray source technologies—polyenergetic dual-energy (PDE) and quasi-monoenergetic x-ray sources (QMXS)—we investigate their trade-offs and future prospects using experimental and simulated results. The reduced scatter and larger separation of low- and high-energy photons provided by QMXS offers improved high-Z material contrast, but practical considerations such as flux and pulse rate need to be solved before making a deployable system. Straight-ray simulations show factor of four increases in contrast for QMXS over PDE scans of tin (Z=50) and iron (Z=26) relative to a uranium plate (Z=92) behind 20 cm of iron simulated cargo.

In x-ray computed tomography (CT) scanning, the presence of metal objects gives rise to artifacts. Although dual-energy CT scanning and decomposition can reduce metal artifacts, in practice, the decomposition is unstable in the presence of noise and yields residual and new artifacts. A common practice in metal artifact reduction (MAR) algorithms is to use a prior-image as a guide to estimating the underlying data that are corrupted by the metal. We have developed a method in which one prior-image can be used to correct the various sinograms generated by dual-energy decomposition. We applied our method to data acquired on a commercial CT scanner. Compared to the uncorrected images, the MAR images have superior uniformity in known uniform regions while preserving edges, and better visual definition of structures.

An adaptive automatic threat recognition system (AATR) developed at the Lawrence Livermore National Laboratory (LLNL) is described for x-ray CT images of baggage. The AATR automatically adapts to the input object requirement specification (ORS), which can change or evolve over time. These specifications characterize materials of interest (MOIs), basic physical features of interest (FOIs) (such a mass and thickness) and performance goals (detection and false alarm probability) for objects of interest (OOIs). The need and technical requirements for an AATR were developed in collaboration with DHS’s Explosives Division and Northeastern University’s Awareness and Localization of Explosives-Related Threats (ALERT) Center, a DHS Center of Excellence (http://www.northeastern.edu/alert/). Independent of the input ORS, LLNL’s AATR always uses the same algorithm and codes to process CT images. The algorithm adapts in real-time to changes in the input ORS. LLNL’s AATR is thus suitable for dynamic scenarios in which the nature of the OOIs can change rapidly. The AATR uses a spatial consensus relaxation method to determine the most likely material composition for each CT image voxel. The resulting image of most likely material compositions is segmented. An OOI classification statistic (OOI score) is computed for each voxel and each extracted image volume. OOI recognition performance is reported using various metrics on a test set of ~180 plastic bins supplied by the ALERT Center of Excellence. A method is then proposed for automatic decision threshold estimation that can adapt to the detection performance goal, the most likely material composition, and the contents of the baggage.

The U.S. Army Research Laboratory, in conjunction with Lawrence Livermore National Laboratory, is developing a Multi-Energy Flash Computed Tomography (MEFCT) diagnostic that will be used to capture tomographic image(s) of dynamic impact and detonation events. To accomplish dynamic tomography, the diagnostic uses numerous source–detector pairs to accumulate up to fifteen two-dimensional images, which are subsequently used to compute up to three three-dimensional tomographic reconstructions. The diagnostic is designed to provide either: a single-frame, three-dimensional tomographic reconstruction that delineates material specificity throughout the field, or a three-frame tomographic reconstruction movie spaced in time, while lacking the information pertaining to the material specificity. This work assesses aspects of the diagnostic development including structural design, dynamic capability, instrument resolution and computational reconstruction. Examples of real-time measurements are provided from static phantom fiducials, as well as a dynamic experiment depicting a non-symmetric ballistic penetration to demonstrate the usefulness of the capability.

Recent advances in cadmium telluride (CdTe) energy-discriminating pixelated detectors have enabled the possibility of Multi-Spectral X-ray Computed Tomography (MSXCT) to incorporate spectroscopic information into CT. MultiX ME 100 V2 is a CdTe-based spectroscopic x-ray detector array capable of recording energies from 20 to 160 keV in 1.1 keV energy bin increments. Hardware and software have been designed to perform radiographic and computed tomography tasks with this spectroscopic detector. Energy calibration is examined using the end-point energy of a bremsstrahlung spectrum and radioisotope spectral lines. When measuring the spectrum from Am-241 across 500 detector elements, the standard deviation of the peak-location and FWHM measurements are ± 0.4 and ± 0.6 keV, respectively. As these values are within the energy bin size (1.1 keV), detector elements are consistent with each other. The count rate is characterized, using a nonparalyzable model with a dead time of 64 ± 5 ns. This is consistent with the manufacturer’s quoted per detector-element linear-deviation at 2 Mpps (million photons per sec) of 8.9 % (typical) and 12 % (max). When comparing measured and simulated spectra, a low-energy tail is visible in the measured data due to the spectral response of the detector. If no valid photon detections are expected in the low-energy tail, then a background subtraction may be applied to allow for a possible first-order correction. If photons are expected in the low-energy tail, a detailed model must be implemented. A radiograph of an aluminum step wedge with a maximum height of 20 mm shows an underestimation of attenuation by about 10 % at 60 keV. This error is due to partial energy deposition from higher energy (>60 keV) photons into a lower-energy (∼60 keV) bin, reducing the apparent attenuation. A radiograph of a polytetrafluoroethylene (PTFE) cylinder taken using a bremsstrahlung spectrum from an x-ray voltage of 100 kV filtered by 1.3 mm Cu is reconstructed using Abel inversion. As no counts are expected in the low energy tail, a first order background correction is applied to the spectrum. The measured linear attenuation coefficient (LAC) is within 10% of the expected value in the 60 to 100 keV range. Below 60 keV, low counts in the corrected spectrum and partial energy deposition from incident photons of energy greater than 60 keV into energy bins below 60 keV impact the LAC measurements. This report ends with a demonstration of the tomographic capability of the system. The quantitative understanding of the detector developed in this report will enable further study in evaluating the system for characterization of an object’s chemical make-up for industrial and security purposes.

We propose a method for material characterization using Spectral X-ray Computed Tomography (SCT). Our SCT method takes advantage of recently-developed MultiX ME 100 photon counting detectors to simultaneously measure the energy dependence of a material's linear attenuation coefficient (LAC). Relative electron density ( ρ e ) and effective atomic number (Ze) are estimated directly from the energy-dependent LAC measurements. The method employs a spectral correction algorithm and automated selection and weighting of the energy bins for optimized performance. When examining materials with Ze ≤ 23, this method achieves accuracy comparable to traditional dual-energy CT, which is often realized through consecutive data acquisitions, and is compatible with any spectral detector. The method disregards data in photon starved energy channels improving the detection of highly attenuating materials, compared to techniques that use energy integrating detectors.

X-ray imaging can be used to inspect cargos imported into the United States. In order to better understand the performance of X-ray inspection systems, the X-ray characteristics (density, complexity) of cargo need to be quantified. In this project, an image complexity measure called integrated power spectral density (IPSD) was studied using both DNDO engineered cargos and stream-of-commerce (SOC) cargos. A joint distribution of cargo density and complexity was obtained. A support vector machine was used to classify the SOC cargos into four categories to estimate the relative fractions.

X-ray inspection systems can be used to detect radiological and nuclear threats in imported cargo. In order to better understand performance of these systems, the attenuation characteristics of imported cargo need to be determined. This project focused on developing image processing algorithms for segmenting cargo and using x-ray attenuation to quantify equivalent steel thickness to determine cargo density. These algorithms were applied to over 450 cargo radiographs. The results are summarized in this report.

In a recent journal article [IEEE Trans. Nuc. Sci., 63(1), 341-350, 2016], we introduced a novel method that decomposes dual-energy X-ray CT (DECT) data into electron density (ρe) and a new effective-atomic-number called Ze in pursuit of system-independent characterization of materials. The Ze of a material, unlike the traditional Zeff, is defined relative to the actual X-ray absorption properties of the constituent atoms in the material, which are based on published X-ray cross sections. Our DECT method, called SIRZ (System-Independent ρe, Ze), uses a set of well-known reference materials and an understanding of the system spectral response to produce accurate and precise estimates of the X-ray-relevant basis variables (ρe, Ze) regardless of scanner or spectra in diagnostic energy ranges (30 to 200 keV). Potentially, SIRZ can account for and correct spectral changes in a scanner over time and, because the system spectral response is included in the technique, additional beam-hardening correction is not needed. Results show accuracy (

Laser experiments, such as those planned at the National Ignition Facility (NIF) and the Omega facility, use small targets with the goal of studying high-energy density physics and inertial confinement fusion. One particular application is a target with layers whose density changes in a carefully designed gradient (from 0.2 to 1.2 g/cm 3 ) for use in isentropic compression experiments (ICE). We are nondestructively determining the density of these layers using two X-ray microscopes. Because of the many interfaces that comprise the layers, a plethora of X-ray phase contrast fringes appear in the images, leading to many radiographic and tomographic artifacts which compromise the ability to infer the density of the layer. In this paper, we describe how we are attacking this problem with a variety of radiographic standards and through radiographic simulation using the HADES radiographic simulation code.

Indirectly driven double shell implosions are being investigated as a possible noncryogenic path to ignition on the National Ignition Facility. Lawrence Livermore National Laboratory has made several technological advances that have produced double shell targets that represent a significant improvement to previously fielded targets. The inner capsule is supported inside the ablator shell by SiO2 aerogel with a nominal density of 50 mg/cm3. The aerogel is cast around the inner capsule and then machined concentric to it. The seamless sphere of aerogel containing the embedded capsule is then assembled between the two halves of the ablator shell. The concentricity between the two shells has been improved to less than 1.5 μm. The ablator shell consists of two hemispherical shells that mate at a step joint that incorporates a gap with a nominal thickness of 0.1 μm. Using a new flexure-based tool holder that precisely positions the diamond cutting tool on the diamond turning machine, step discontinuities...

The goal of “as-built” computational modeling is to incorporate the most representative geometry and material information for an (fabricated or legacy) object into simulations. While most engineering finite element simulations are based on an object’s idealized “as-designed” configuration with information obtained from technical drawings or computer-aided design models, as-built modeling uses nondestructive characterization and metrology techniques to provide the feature information. By incorporating more representative geometry and material features as initial conditions, the uncertainty in the simulation results can be reduced, providing a more realistic understanding of the event and object being modeled. In this paper, key steps and technology areas in the as-built modeling framework are: (1) inspection using nondestructive characterization and metrology techniques; (2) data reduction (signal and image processing including artifact removal, data sensor fusion, and geometric feature extraction); and (3) engineering and physics analysis using finite element codes. We illustrate the process with a cylindrical phantom and include a discussion of the key concepts and areas that need improvement. Our results show that reasonable as-built initial conditions based on a volume overlap criteria can be achieved and that notable differences between simulations of the as-built and as-designed configurations can be observed for a given load case. Specifically, a volume averaged difference of accumulated plastic strain of 3% and local spatially varying differences up to 10%. The example presented provides motivation and justification to engineering teams for the additional effort required in the as-built modeling of high value parts. Further validation of the approach has been proposed as future work.

A gamma-ray-based, active (A) and passive (P) computed tomography (CT) technology has been developed that locates, identifies and quantifies gamma-ray emitting isotopes, transuranic (TRU) and others, in nuclear waste drums. ACT uses a collimated external source and a HPGe detector to measure selected mono-energetic gamma-rays that are attenuated by waste-drum contents; a separate PCT measurement uses the HPGe detector to record the spectra of gamma-rays emitted from within a drum. The ACT attenuation images and the PCT emission spectra are coupled to quantitatively assay drum contents for ∼0.1–200 g of TRU isotopes. Calibration requires a single measurement of a known radioactive standard; construction of waste-drum surrogates is not required. Fixed and mobile systems demonstrated compliance with a DOE quality assurance program via several independent blind tests.

We developed a method to evaluate the accuracy of segmentation algorithms. Oversegmentation, undersegmentation, missing and spurious labels may all appear concurrently in machine segmented images. Segmentation algorithms make systematic errors and have different optimal operating ranges. Existing methods of segmentation evaluation do not evaluate these details. Our method, based on multiple feature recovery, reports systematic errors and indicates optimal operating ranges of features, besides measuring overall errors. A knowledge of the magnitude and type of errors can be used for tuning or selecting segmentation algorithms. Although our method was developed for CT scanning for security, it is applicable to other fields, including medical imaging, where multi-object feature recovery, non-uniform costs and a knowledge of optimal operating ranges are helpful.

Author(s): Karimi, Seemeen; Jiang, Xiaoqian; Cosman, Pamela; Martz, Harry | Abstract: BackgroundImaging systems used in aviation security include segmentation algorithms in an automatic threat recognition pipeline. The segmentation algorithms evolve in response to emerging threats and changing performance requirements. Analysis of segmentation algorithms' behavior, including the nature of errors and feature recovery, facilitates their development. However, evaluation methods from the literature provide limited characterization of the segmentation algorithms.ObjectiveTo develop segmentation evaluation methods that measure systematic errors such as oversegmentation and undersegmentation, outliers, and overall errors. The methods must measure feature recovery and allow us to prioritize segments.MethodsWe developed two complementary evaluation methods using statistical techniques and information theory. We also created a semi-automatic method to define ground truth from 3D images. We applied our methods to evaluate five segmentation algorithms developed for CT luggage screening. We validated our methods with synthetic problems and an observer evaluation.ResultsBoth methods selected the same best segmentation algorithm. Human evaluation confirmed the findings. The measurement of systematic errors and prioritization helped in understanding the behavior of each segmentation algorithm.ConclusionsOur evaluation methods allow us to measure and explain the accuracy of segmentation algorithms.

Metal artifact reduction methods in computed tomography replace the projection data passing through metals with an estimate of the true data. Inaccurate estimation leads to the generation of secondary artifacts. Data estimates can be improved by the use of prior knowledge of the projection data. In this paper, a method has been created to generate a prior image. The method uses computer vision techniques to segment regions of the initially reconstructed image and then discriminates between regions that are likely to be artifacts and anatomical structures. Results on test images show that metal artifacts are reduced and that few secondary artifacts are present, even in the case of multiple metal objects.

We are developing a new technique using both active (A) and passive (P) computed tomography (CT) to overcome problems in the quantitative analysis of plutonium contents in the molten salt extract (MSE) plutonium buttons. Our first three dimensional image of the MSE button using ACT scan has already shown heterogeneous behavior throughout the button as opposed to the model of a homogeneous button as previously thought. An image from a PCT scan, although it does not have sufficient spatial resolution and data, also seems to support the heterogeneous picture.

The US Department of Homeland Security (DHS) has requirements for future explosives scanners that include dealing with a larger number of threats, higher probability of detection, lower false alarm rates and lower operating costs. One tactic that DHS is pursuing to achieve these requirements is to augment the capabilities of the established security vendors with third-party algorithm developers. The purposes of this presentation are to review DHS's objectives for involving third parties in the development of advanced algorithms and then to discuss how these objectives are achieved using workshops and grand challenges.

Gamma-ray computed tomography (CT) is potentially powerful nondestructive method for assessing the degree of distress that exists in reinforced-concrete structures. In a study to determine the feasibility of using CT to inspect reinforced-concrete specimens, we verified that CT can quantitatively image the internal details of reinforced concrete. To assess the accuracy of CT in determining voids and cracks, we inspected two fiber-reinforced concrete cylinders (one loaded and one unloaded) and a third cylinder containing a single reinforcing bar (rebar). To evaluate the accuracy of CT in establishing the location of reinforcing bars, we also inspected a concrete block containing rebars with different diameters. The results indicate that CT was able to revolve the many different phases in reinforced concrete (voids, cracks, rebars, and concrete) with great accuracy. 15 refs., 10 figs.

X-ray computerized tomography (CAT or CT) is a sophisticated imaging technique that provides cross-sectional views of materials, components and assemblies for industrial nondestructive evaluation (NDE). We have studied the feasibility of using CT as an inspection tool for reinforced concrete and the use of multi-energy, linear, attenuation techniques to deduce variations in density (ρ) and/or atomic number (Z) that could be caused by varying the types of concrete mixes and/or compaction in the concrete itself. To perform this study, we designed and built a prototype medium-/high-energy (200- to 2000 keV) CT scanner — ZCAT — to image small concrete samples (± 30 cm in diameter and ± 75 cm in height) with a spatial resolution of about 2 mm. We used ZCAT to quantitatively inspect a 20 cm concrete cube with 1.27 cm diameter reinforcing bars (rebars) and to measure p and/or Z variations in a 20 cm diameter concrete cylinder. We describe the ZCAT scanner design, some of its physical limitations and the data-acquisition parameters used in our study. Our results and those of others [1,2] show that CT can be used to inspect reinforced concrete and to distinguish material p and/or Z variations within concrete.

x-Ray computed axial tomography (CT) provides cross-sectional views of materials, components, and assemblies for industrial non-destructive evaluation. We have applied CT imaging to quantitatively measure the 3-D distribution ogf x-ray attenuation at reasonably high resolutions. In our industrial x-ray CT-studies, we have centered on two technical approaches: a first-generation translate/rotate CT system that consist of well-collimated (∼ 0.55 mm) photon source detector, and a third-generation scanner that uses a fluoroscopy detector.

The mix between x-ray phase and attenuation information needs to be understood for accurate object recovery from radiography and tomography data. We are researching and experimentally validating algorithms that simulate x-ray phase contrast to determine the required physics necessary for quantitative object recovery. The results of a study are described to determine if a multislice (beam-propagation) method is required for simulating x-ray radiographs. We conclude that the multislice method is not required for accurate simulation of greater than or equal to 8 keV x-ray radiographs of millimeter-size objects with micrometer structures.

Summary form only given. We demonstrate phase-contrast enhanced X-ray imaging (PCXI) for characterization of the solid deuterium-tritium surface inside of beryllium shells. This novel method of X-ray imaging takes advantage of the small refraction and diffraction of the X-rays at boundaries between materials. PCXI is more sensitive to small density changes in low atomic number materials than traditional absorption radiography. Point-projection X-ray microscopes were used in our laboratory to study the surface roughness of a solid deuterium-tritium layer inside of a beryllium capsule. This method can also be applied to plasma physics characterization

High energy density experiments, such as those planned at the National Ignition Facility (NIF), use mesoscale targets with the goals of studying high energy density physics, inertial confinement fusion, and the support of national security needs. Mesoscale targets are typically several millimeters in size and have complex micrometer‐sized structures composed of high‐density metals and low‐density foams and ices. These targets are designed with exacting tolerances that are difficult to achieve at present. Deviation from these tolerances can result in compromise of experimental goals and thus it is necessary to determine as‐built properties of these targets using NDE techniques. Radiography and computed tomography are being used to investigate these targets, but the mix between phase and absorption information is difficult to separate, making interpretation of results difficult. We have recently improved the HADES radiographic simulation code to include phase in simulations, as an aid for doing NDE on mesos...

A high-speed Radon transform computer (RTC) has been designed and simulated that operates on the principles of the parallel projection pipeline engine (PPPE) processor suggested by J.L.C. Sanz, et al. (1988). The computer consists of an array of identical processing elements with fast communication links to each of its neighbors and uses forward- and back-projection formulas tests linear interpolation. Simulation and experimental timing tests have been performed on both a systolic array of 64 transputer processors and on arrays of commercial DSP (digital signal processor) chips. A custom VLSI implementation is currently under design which is expected to perform forward and inverse transforms of 512 by 512 images at or near video rates. >

The failure of a steel pipe subjected to shock loading was observed using x ray imaging. We describe and analyze the x ray images in detail. We see radiographic evidence that most of the fractures were due to shear rather than brittle failure. We also make quantitative comparisons between static radiographs and simulations but do not see perfect agreement. The sources of the current lack of agreement are discussed, as well as future work planned.

We have developed a new tomography code, HADES-CCG. This code uses HADES, a radiographic simulation code, to perform forward- and back-projection and is coupled to a Constrained Conjugate Gradient (CCG) optimizer. An iterative solution to the reconstruction problem is found which is optimal, given the detector noise model, a source model and the appropriate attenuation cross-sections. By explicitly including experimental effects in forward- and back-projection, these effects are not folded back into the object model.

Computed Tomography (CT) using penetrating radiation (x- or gamma-rays) can be used in a number of aircraft applications. This technique results in 3D volumetric attenuation data that is related to density and effective atomic number. CT is a transmission scanning method that must allow complete access to both sides of the object under inspection; the radiation source and detection systems must surround the object. This normally precludes the inspection of some large or planar (large aspect ratio) parts of the aircraft. However, we are pursuing recent limited-data techniques using object model information to obtain useful data from the partial information acquired. As illustrative examples, we describe how CT was instrumental in the analysis of particular aircraft components. These include fuselage panels, single crystal turbine blades, and aluminum-lithium composites.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Members of the Nondestructive Evaluation Section at the Lawrence Livermore National Laboratory (LLNL) are implementing the advanced three-dimensional imaging technique of x- and gamma-ray computed tomography (CAT or CT) for industrial and scientific obscured object evaluation. This technique provides internal and external views of materials, components, and assemblies nonintrusively. Our work includes building of CT scanners as well as data preprocessing, image reconstruction, display and analysis algorithms. These capabilities have been applied to a variety of industrial and scientific NDE applications. We have used CT to study various objects with obscured features at our laboratory ranging in size from 1 mm3 to 1 m3. In these studies, CT has revealed flaws (e.g. cracks, voids, and inclusions), internal and external dimensional information, differences in elemental composition or material density, and other important material characteristics. CT has also been used to localize, identify, and quantify radioisotopes within canisters. As illustrative examples, we describe how CT was instrumental in the analysis of concrete specimens, diesel engine thermocouple plugs, jet engine turbine blades, ballistic target materials, and radioactive waste canisters.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Considerable effort is being applied to develop multiple-energy industrial CT techniques for materials characterization. Multiple-energy CT can provide reliable estimates of effective Z (Z{sub eff}), weight fraction, and rigorous calculations of absolute density, all at the spatial resolution of the scanner. Currently, a wide variety of techniques exist for CT scanners, but each has certain problems and limitations. Ultimately, the best multi-energy CT technique would combine the qualities of accuracy, reliability, and wide range of application, and would require the smallest number of additional measurements. We have developed techniques for calculating material properties of industrial objects that differ somewhat from currently used methods. In this paper, we present our methods for calculating Z{sub eff}, weight fraction, and density. We begin with the simplest case -- methods for multiple-energy CT using isotopic sources -- and proceed to multiple-energy work with x-ray machine sources. The methods discussed here are illustrated on CT scans of PBX-9502 high explosives, a lexan-aluminum phantom, and a cylinder of glass beads used in a preliminary study to determine if CT can resolve three phases: air, water, and a high-Z oil. In the CT project at LLNL, we have constructed several CT scanners of varying scanning geometries usingmore » {gamma}- and x-ray sources. In our research, we employed two of these scanners: pencil-beam CAT for CT data using isotopic sources and video-CAT equipped with an IRT micro-focal x-ray machine source.« less

Proton beams with energies of 5 and 7 MeV are focused to 5 μm and used to produce tomograms of capillary tubes and low-density foams. In this energy range, proton energy loss is primarily due to interactions with electrons. Therefore, by measuring the residual energy of protons transmitted through samples in a manner similar to that used for Scanning Transmission Ion Microscopy (STIM), and reconstructing a cross-sectional image from multiple projections, we can map out spatial variations in electron density due to sample geometry and composition. In our experimental arrangement, the sample is translated and rotated in a stationary proton beam. Transmitted proton energies are measured using a silicon surface barrier detector. Tomographie reconstructions are produced from the calculated line-average densities using a procedure based on a filtered backprojection algorithm developed for X-ray computed tomography (CT) systems. The technique is especially useful in characterizing samples where large variations in Z or low total density limit the applicability of X-ray CT analysis.