Mineral quantitative characterization method based on basis material decomposition model by dual-energy computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) can reconstruct electron density ρe and effective atomic number Zeff distribution for material discrimination. Image-domain basis material decomposition (IBMD) method is a widely used DECT method. However, IBMD method cannot be used for mineral identification directly due to limitations of complex basis material determination, beam hardening artifacts, and inherent errors caused by approximate empirical formulas. OBJECTIVE: This study proposes an improved IBMD (IIBMD) method to overcome the above limitations. METHODS: In IIBMD method, the composition of basis material is optimized to obtain accurate decomposition coefficients, which enables accurate ρe and Zeff distribution. Moreover, the thickness of basis material is optimized to reduce the effect of beam hardening. Furthermore, two formulas in place of empirical formulas are proposed to calculate ρe and Zeff. Finally, a threshold technique is applied to separate different mineral phases. RESULTS: Numerical simulations and practical experiments using a photon-counting detector CT system are implemented to verify IIBMD method. Results show that the relative errors of ρe and Zeff for seven common minerals are down to 5%, lower than most of the existing DECT methods for rocks. Reasonable volume fraction results of mineral phases are thus obtained through threshold segmentation. CONCLUSIONS: This study demonstrates that the proposed IIBMD method has high practical value in mineralogical identification.

The Detection of Foreign Items in Laundry Industry by Dual-Energy X-ray Transmission-Advantages and Limits.

Firefighters, paramedics, nursing staff, and other occupational groups are in constant need of fast and proper cleaning of their professional workwear, not only during a pandemic. Thus, laundry technology needs to become more efficient and automated. Unfortunately, some steps of the cleaning process, such as finding and removing foreign items from pockets or belts, are still completed manually. This is not just time-consuming but potentially dangerous for the workers due to the hazardous nature of items such as scissors, scalpels, or syringes. Additionally, some items may damage the garments by staining or harm the laundry machines, causing malfunctions and process failure. On the one hand, these foreign items are often hidden inside the clothes, making detection very challenging with conventional superficial sensors. On the other hand, these items can be diverse and cannot be detected by metal detectors alone. X-ray transmission has proven to be a powerful tool for detecting items inside of objects. The dual-energy approach (DE-XRT) even allows obtaining quantitative information about the chemical composition of the measured materials. In this study, working garments were accompanied and filled with realistic foreign items. The potential of DE-XRT to detect those items was successfully shown.

Potential of Dual and Multi Energy XRT and CT Analyses on Iron Formations.

Dual and multi energy X-ray transmission imaging (DE-/ME-XRT) are powerful tools to acquire quantitative material characteristics of diverse samples without destruction. As those X-ray imaging techniques are based on the projection onto the imaging plane, only two-dimensional data can be obtained. To acquire three-dimensional information and a complete examination on topology and spatial trends of materials, computed tomography (CT) can be used. In combination, these methods may offer a robust non-destructive testing technique for research and industrial applications. For example, the iron ore mining and processing industry requires the ratio of economic iron minerals to siliceous waste material for resource and reserve estimations, and for efficient sorting prior to beneficiation, to avoid equipment destruction due to highly abrasive quartz. While XRT provides information concerning the thickness, areal density and mass fraction of iron and the respective background material, CT may deliver size, distribution and orientation of internal structures. Our study shows that the data provided by XRT and CT is reliable and, together with data processing, can be successfully applied for distinguishing iron oxide rich parts from waste. Furthermore, heavy element bearing minerals such as baryte, uraninite, galena and monazite can be detected.

Microscopic dual-energy CT (microDECT): a flexible tool for multichannel ex vivo 3D imaging of biological specimens.

Dual-energy computed tomography (DECT) uses two different x-ray energy spectra in order to differentiate between tissues, materials or elements in a single sample or patient. DECT is becoming increasingly popular in clinical imaging and preclinical in vivo imaging of small animal models, but there have been only very few reports on ex vivo DECT of biological samples at microscopic resolutions. The present study has three main aims. First, we explore the potential of microscopic DECT (microDECT) for delivering isotropic multichannel 3D images of fixed biological samples with standard commercial laboratory-based microCT setups at spatial resolutions reaching below 10 µm. Second, we aim for retaining the maximum image resolution and quality during the material decomposition. Third, we want to test the suitability for microDECT imaging of different contrast agents currently used for ex vivo staining of biological samples. To address these aims, we used microCT scans of four different samples stained with x-ray dense contrast agents. MicroDECT scans were acquired with five different commercial microCT scanners from four companies. We present a detailed description of the microDECT workflow, including sample preparation, image acquisition, image processing and postreconstruction material decomposition, which may serve as practical guide for applying microDECT. The MATLAB script (The Mathworks Inc., Natick, MA, USA) used for material decomposition (including a graphical user interface) is provided as a supplement to this paper (https://github.com/microDECT/DECTDec). In general, the presented microDECT workflow yielded satisfactory results for all tested specimens. Original scan resolutions have been mostly retained in the separate material fractions after basis material decomposition. In addition to decomposition of mineralized tissues (inherent sample contrast) and stained soft tissues, we present a case of double labelling of different soft tissues with subsequent material decomposition. We conclude that, in contrast to in vivo DECT examinations, small ex vivo specimens offer some clear advantages regarding technical parameters of the microCT setup and the use of contrast agents. These include a higher flexibility in source peak voltages and x-ray filters, a lower degree of beam hardening due to small sample size, the lack of restriction to nontoxic contrast agents and the lack of a limit in exposure time and radiation dose. We argue that microDECT, because of its flexibility combined with already established contrast agents and the vast number of currently unexploited stains, will in future represent an important technique for various applications in biological research.

A practical material decomposition method for x-ray dual spectral computed tomography.

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

Iterative dual energy material decomposition from spatial mismatched raw data sets.

Today's clinical dual energy computed tomography (DECT) scanners generally measure different rays for different energy spectra and acquire spatial mismatched raw data sets. The deficits in clinical DECT technologies suggest that mainly image based material decomposition methods are in use nowadays. However, the image based material decomposition is an approximate technique, and beam hardening artifacts remain in decomposition results. A recently developed image based iterative method for material decomposition from inconsistent rays (MDIR) can achieve much better image quality than the conventional image based methods. Inspired by the MDIR method, this paper proposes an iterative method to indirectly perform raw data based DECT even with completely mismatched raw data sets. The iterative process is initialized by density images that were obtained from an image based material decomposition. Then the density images are iteratively corrected by comparing the estimated polychromatic projections and the measured polychromatic projections. Only three iterations of the method are sufficient to greatly improve the qualitative and quantitative information in material density images. Compared with the MDIR method, the proposed method needs not to perform additional water precorrection. The advantages of the method are verified with numerical experiments from inconsistent noise free and noisy raw data.

Dual-energy computed tomography imaging with megavoltage and kilovoltage X-ray spectra.

Purpose: Single-energy computed tomography (CT) often suffers from poor contrast yet remains critical for effective radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) X-ray sources and thus already possess hardware for dual-energy (DE) CT. There is unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts. Approach: A single-line integral toy model was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (3 kV, 2 MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images. Results: The 80 kV-140 kV pair typically yielded the best SNRs, but for bone thicknesses >8 cm, the detunedMV-80 kV pair surpassed it. Peak MV-kV SNR was achieved with ∼90% dose allocated to the MV spectrum. In CT simulations of the pelvis with a steel implant, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT and kV-kV DE-CT. Without steel, the MV-kV VMIs produced higher contrast but lower CNR than single-energy CT. Conclusions: This work analyzes MV-kV DE-CT imaging and assesses its potential advantages. The technique may be used for metal artifact correction and generation of VMIs with higher native contrast than single-energy CT. Improved denoising is generally necessary for greater CNR without metal.

Dual-energy x-ray approach for object/energy-specific attenuation coefficient correction in single-photon emission computed tomography: effects of contrast agent.

Purpose: To investigate the influence of radiographic contrast agent on the accuracy of the photon counts arising from the emission of gamma rays of radionuclides in single-photon emission computed tomography (SPECT), when dual-energy x-ray CT (DXCT) is employed for providing object/energy-specific attenuation coefficient correction in SPECT. Approach: Computer simulation was performed for three transmission CT approaches, namely, the conventional (single kVp, unimodal spectrum) x-ray CT, DXCT (single kVp, bimodal spectrum) with basis material decomposition (BMD), and DXCT with BMD followed by basis material coefficients transformation (BMT), to study the effects of these approaches on the accuracy of the photon counts from the SPECT image of a thorax-like phantom. Results: All three CT approaches revealed that the error in the counts was both photon energy and iodine concentration-dependent. Differences in the trending increase/decrease in the errors with the respective increase in iodine concentration and photon energy were observed among the three CT approaches. Of the three, the BMT/SPECT approach resulted in the smallest error in the concentration of radionuclides measured, especially in the contrast agent-filled region, and the optimal level depended on the iodine concentration and photon energy. Conclusion: With a judicious choice of the basis materials and photon energy, it may be possible to take advantage of the benefits of the BMT method to mitigate the accuracy problem in DXCT for quantitative SPECT imaging.

Three-Material Decomposition in Multi-energy CT: Impact of Prior Information on Noise and Bias.

In order to perform material decomposition for a three-material mixture, dual-energy CT (DECT) has to incorporate an additional condition, typically the prior information related to certain physical constraints such as volume or mass conservation. With the introduction of photon-counting CT and other multi-energy CT (MECT) platform, more than 2 energy bins can be simultaneously acquired, which in principle can solve a three-material problem without the need of additional prior information. The purpose of this work was to investigate the impact of prior information on noise and bias properties of three-material decomposition in both DECT and MECT, and to evaluate if the prior information is still needed in MECT. Computer simulation studies were performed to compare basis image noise and quantification accuracy among DECT with prior information, and MECT with/without prior information. For given spectral configurations, the simulation results showed that significant noise reductions can be achieved in all the basis material images when prior information was included in the material decomposition process. Compared to DECT with prior information, MECT (N=3) with prior information had slightly better noise performance due to additional beam measurement and well preserved spectral separation. In addition, when wrong prior information ([-2.0%, 2.0%]) was intentionally introduced, the quantification accuracy evaluated by root-mean-square-error (RMSR) using MECT with prior information was less than 1.5mg/cc for gadolinium quantification and 1.2mg/cc for iodine quantification.

Dual-source multienergy CT with triple or quadruple x-ray beams.

Energy-resolved photon-counting-detector CT (PCD-CT) is promising for material decomposition with multiple contrast agents using two or more energy bins. However, corrections for nonidealities of PCDs are required, which are still active research topics. In addition, PCD-CT is also likely to have a very high cost due to the current lack of mass production capabilities. We proposed an alternative approach to perform multienergy CT (MECT), which is achieved by acquiring triple or quadruple x-ray beam measurements on a dual-source CT scanner. This strategy was based on a "twin-beam" design on a single-source scanner for dual-energy CT. Examples of beam filters and spectra for triple and quadruple x-ray beam were provided. Computer simulation studies were performed to evaluate the noise and accuracy of material decomposition for multiple contrast mixtures using both triple- and quadruple-beam configurations, compared with the performance on a PCD-CT platform. The results demonstrated that the image quality and dose efficiency of the triple-beam configuration in the proposed MECT technique were comparable to that in PCD-CT. The proposed technique can be readily implemented on a dual-source scanner, which may allow material decomposition of multiple contrast agents to be performed on clinical CT scanners with energy-integrating detectors.

Bias-variance tradeoff in anticorrelated noise reduction for spectral CT.

PURPOSE: In spectral CT, basis material decomposition is commonly used to generate a set of basis images showing the material composition at each point in the field of view. The noise in these images typically contains anticorrelations between the different basis images, which leads to increased noise in each basis image. These anticorrelations can be removed by changing the basis functions used in the material decomposition, but the resulting basis images can then no longer be used for quantitative measurements. Recent studies have demonstrated that reconstruction methods which take the anticorrelations into account give reduced noise in the reconstructed image. The purpose of this work is to analyze an analytically solvable denoising model problem and investigate its effect on the noise level and bias in the image as a function of spatial frequency. METHOD: A denoising problem with a quadratic regularization term is studied as a mathematically tractable model for such a reconstruction method. An analytic formula for the resulting image in the spatial frequency domain is presented, and this formula is applied to a simple mathematical phantom consisting of an iodinated contrast agent insert embedded in soft tissue. We study the effect of the denoising on the image in terms of its transfer function and the visual appearance, the noise power spectrum and the Fourier component correlation coefficient of the resulting image, and compare the result to a denoising problem which does not model the anticorrelations in the image. RESULTS: Including the anticorrelations in the noise model of the denoising method gives 3-40% lower noise standard deviation in the soft-tissue image while leaving the iodine standard deviation nearly unchanged (0-1% difference). It also gives a sharper edge-spread function. The studied denoising method preserves the noise level and the anticorrelated structure at low spatial frequencies but suppresses the noise and removes the anticorrelations at higher spatial frequencies. Cross-talk between images gives rise to artifacts at high spatial frequencies. CONCLUSIONS: Modeling anticorrelations in a denoising problem can decrease the noise level in the basis images by removing anticorrelations at high spatial frequencies while leaving low spatial frequencies unchanged. In this way, basis image cross-talk does not lead to low spatial frequency bias but it may cause artifacts at edges in the image. This theoretical insight will be useful for researchers analyzing and designing reconstruction algorithms for spectral CT.

Dual-Energy Computed Tomography: Physical Principles, Approaches to Scanning, Usage, and Implementation: Part 2.

There are increasing applications and use of spectral computed tomography or dual-energy computed tomography (DECT) in neuroradiology and head and neck imaging in routine clinical practice. Part 1 of this 2-part review covered fundamental physical principles underlying DECT scanning and the different approaches for scanning. Part 2 focuses on important and practical considerations for implementing and using DECT in clinical practice, including a review of different images and reconstructions produced by these scanners and important and practical issues, ranging from image quality and radiation dose to workflow-related aspects of DECT scanning, that routinely come up during operationalization of DECT.

Dual-Source Multi-Energy CT with Triple or Quadruple X-ray Beams.

Energy-resolved photon-counting CT (PCCT) is promising for material decomposition with multi-contrast agents. However, corrections for non-idealities of PCCT detectors are required, which are still active research areas. In addition, PCCT is associated with very high cost due to lack of mass production. In this work, we proposed an alternative approach to performing multi-energy CT, which was achieved by acquiring triple or quadruple x-ray beam measurements on a dual-source CT scanner. This strategy was based on a "Twin Beam" design on a single-source scanner for dual-energy CT. Examples of beam filters and spectra for triple and quadruple x-ray beam were provided. Computer simulation studies were performed to evaluate the accuracy of material decomposition for multi-contrast mixtures using a tri-beam configuration. The proposed strategy can be readily implemented on a dual-source scanner, which may allow material decomposition of multi-contrast agents to be performed on clinical CT scanners with energy-integrating detector.

An extended simultaneous algebraic reconstruction technique (E-SART) for X-ray dual spectral computed tomography.

X-ray dual spectral computed tomography (DSCT) scans the measured object with two different x-ray energy spectra and the collected polychromatic projections from this procedure can be used to perform basis material decomposition of the object. An iterative method E-ART was recently proposed to produce highly quantitative basis material images for DSCT, but it has the drawback of slow convergence and huge computational costs. Inspired by the E-ART method, this paper proposes an extended simultaneous algebraic reconstruction technique (E-SART) for the basis material decomposition of DSCT and an accelerating strategy for improve the convergence speed of the iterative reconstruction. Compared with the E-ART method, the proposed method has much faster convergence rate while at the same time it has better noise suppressing feature. The advantages of this method were verified by experiments in which the FORBILD thorax phantom was iteratively reconstructed from noise-free and noisy polychromatic projections. SCANNING 38:599-611, 2016. © 2016 Wiley Periodicals, Inc.