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In 2016, we published a method for processing dual-energy computed tomography (DECT) data called system-independent rho-e/Z-e ( $\rho _{\mathrm {e}}/Z_{\mathrm {e}}$ ) or SIRZ. Using data from multiple DECT systems and spectra, SIRZ estimated the electron density $\rho _{\mathrm {e}}$ and effective atomic number $Z_{\mathrm {e}}$ (based on published X-ray cross sections), for a set of known specimens. However, the decomposition process required complex spectral modeling of the DECT system, which made SIRZ difficult to implement and automate. This paper describes the subsequent work on “SIRZ-2” to simplify the spectral modeling, automate the process, and improve its range and versatility. The SIRZ-2 basis functions are more accurate for the X-ray energy range ( $Z_{\mathrm {e}}$ of 6–20) were scanned with multiple spectral pairs (up to 200 keV) on seven different DECT systems, including a commercial airport luggage scanner. For these varied tests, the average SIRZ-2 relative errors for $\rho _{\mathrm {e}}$ estimates were four times lower (0.7% compared to 3.0% for SIRZ), while average $Z_{\mathrm {e}}$ relative errors were comparably low for both methods ( $\rho _{\mathrm {e}}$ , $Z_{\mathrm {e}}$ ) that can be directly compared across DECT systems and over time.

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.

We present a new decomposition approach for dual-energy computed tomography (DECT) called SIRZ that provides precise and accurate material description, independent of the scanner, over diagnostic energy ranges (30 to 200 keV). System independence is achieved by explicitly including a scanner-specific spectral description in the decomposition method, and a new X-ray-relevant feature space. The feature space consists of electron density, ${\rho _{\rm e}}$ , and a new effective atomic number, ${{\rm Z}_{\rm e}}$ , which is based on published X-ray cross sections. Reference materials are used in conjunction with the system spectral response so that additional beam-hardening correction is not necessary. The technique is tested against other methods on DECT data of known specimens scanned by diverse spectra and systems. Uncertainties in accuracy and precision are less than 3% and 2% respectively for the ( ${\rho _{\rm e}}$ , ${{\rm Z}_{\rm e}}$ ) results compared to prior methods that are inaccurate and imprecise (over 9%).

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.

These are slides about in-situ X-ray CT results of damage evolution in L6 ordinary chondrite meteorites. The following topics are covered: mechanical and thermal damage characterization, list of Grosvenor Mountain (GRO) meteorite samples, in-situ x-ray compression test setup, GRO-chipped reference at 0 N - existing cracks, GRO-chipped loaded at 1580 N, in-situ x-ray thermal fatigue test setup, GRO-B14 room temperature reference, GRO-B14 Cycle 47 at 200°C, GRO-B14 Cycle 47 at room temperature, conclusions from qualitative analysis, future work and next steps. Conclusions are the following: Both GRO-Chipped and GRO-B14 had existing voids and cracks within the volume. These sites with existing damage were selected for CT images from mechanically and thermally loaded scans since they are prone to damage initiation. The GRO-Chipped sample was loaded to 1580 N which resulted in a 14% compressive engineering strain, calculated using LVDT. Based on the CT cross sectional images, the GRO-B14 sample at 200°C has a thermal expansion of approximately 96 μm in height (i.e. ~1.6% engineering strain).

Purpose: Metal objects present in x-ray computed tomography(CT) scans are accompanied by physical phenomena that render CT projections inconsistent with the linear assumption made for analytical reconstruction. The inconsistencies create artifacts in reconstructed images. Metal artifact reduction algorithms replace the inconsistent projection data passing through metals with estimates of the true underlying projection data, but when the data estimates are inaccurate, secondary artifacts are generated. The secondary artifacts may be as unacceptable as the original metal artifacts; therefore, better projection data estimation is critical. This research uses computer vision techniques to create better estimates of the underlying projection data using observations about the appearance and nature of metal artifacts. Methods: The authors developed a method of estimating underlying projection data through the use of an intermediate image, called the prior image. This method generates the prior image by segmenting regions of the originally reconstructed image, and discriminating between regions that are likely to be metal artifacts and those that are likely to represent anatomical structures. Regions identified as metal artifact are replaced with a constant soft-tissue value, while structures such as bone or air pockets are preserved. This prior image is reprojected (forward projected), and the reprojections guide the estimation of the underlying projection data using previously published interpolation techniques. The algorithm is tested on head CT test cases containing metal implants and compared against existing methods. Results: Using the new method of prior image generation on test images, metal artifacts were eliminated or reduced and fewer secondary artifacts were present than with previous methods. The results apply even in the case of multiple metal objects, which is a challenging problem. The authors did not observe secondary artifacts that were comparable to or worse than the original metal artifacts, as sometimes occurred with the other methods. The accuracy of the prior was found to be more critical than the particular interpolation method. Conclusions: Metals produce predictable artifacts in CTimages of the head. Using the new method, metal artifacts can be discriminated from anatomy, and the discrimination can be used to reduce metal artifacts.

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...

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.

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.

The purpose of this Standard Operating Procedure (SOP) is to give guidelines on how to determine the density of a sample that will be used as the requirement density. This will be the requirement density of record for the specimens examined by Micro CT and EDS measurements. This density will then be set as the formulation requirement for radiography measurements. This SOP is referred to in TP 48— Preparation of Hydrogen Peroxide/Icing Sugar Specimens for X-ray Measurements by J. G. Reynolds and H. E. Martz.

The purpose of this Standard Operating Procedure (SOP) is to give guidelines on how to measure the volume of a container for use in radiography studies. This SOP gives details on a recommended method of how exactly to measure the volume of containers used for specimens for Micro CT and EDS measurements. This volume is important in determining accurate densities of the specimens. This SOP is referred to in TP 48 - Preparation of Hydrogen Peroxide/Icing Sugar Specimens for X-ray Measurements by J.G. Reynolds and H.E. Martz

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...

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.

The development and improvement of advanced materials is strictly connected to the understanding of the properties and behavior of such materials as a function of both their macro and micro-structures. The application of X-ray computed tomography (CT) to these materials allows for a better understanding of the materials properties and behavior on either macro or micro-structure scales. The authors applied CT to study a set of aerospace grade carbon fiber/thermoplastic matrix composites. Samples of APC-2 (PEEK/AS4) were subjected to either static or high-stress fatigue loading in tension. Both notched (central circular hole) and unnotched specimens were examined. They are investigating a high-temperature thermoplastic polyimide composite sample by acquiring CT data sets before, during (at set intervals), and after full-reversal (tension-compression), low-stress fatigue loading at the upper use temperature. The CT scanner employed and the results obtained in the analysis of 3D CT data sets to study the defects and other features within the different composites are presented in this report.

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.

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