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At least 109 records · Page 6

Robust primary modulation-based scatter estimation for cone-beam CT

Purpose: Scattered radiation is one of the major problems facing image quality in flat detector cone-beam computed tomography (CBCT). Previously, a new scatter estimation and correction method using primary beam modulation has been proposed. The original image processing technique used a frequency-domain-based analysis, which proved to be sensitive to the accuracy of the modulator pattern both spatially and in amplitude as well as to the frequency of the modulation pattern. In addition, it cannot account for penumbra effects that occur, for example, due to the finite focal spot size and the scatter estimate can be degraded by high-frequency components of the primary image. Methods: In this paper, the authors present a new way to estimate the scatter using primary modulation. It is less sensitive to modulator nonidealities and most importantly can handle arbitrary modulator shapes and changes in modulator attenuation. The main idea is that the scatter estimation can be expressed as an optimization problem, which yields a separation of the scatter and the primary image. The method is evaluated using simulated and experimental CBCT data. The scattering properties of the modulator itself are analyzed using a Monte Carlo simulation. Results: All reconstructions show strong improvements of image quality. To quantify the results, all images are compared to reference images (ideal simulations and collimated scans). Conclusions: The proposed modulator-based scatter reduction algorithm may open the field of flat detector-based imaging to become a quantitative modality. This may have significant impact on C-arm imaging and on image-guided radiation therapy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hybrid radiosity-SP{sub 3} equation based bioluminescence tomography reconstruction for turbid medium with low- and non-scattering regions

To provide an ideal solution for a specific problem of gastric cancer detection in which low-scattering regions simultaneously existed with both the non- and high-scattering regions, a novel hybrid radiosity-SP{sub 3} equation based reconstruction algorithm for bioluminescence tomography was proposed in this paper. In the algorithm, the third-order simplified spherical harmonics approximation (SP{sub 3}) was combined with the radiosity equation to describe the bioluminescent light propagation in tissues, which provided acceptable accuracy for the turbid medium with both low- and non-scattering regions. The performance of the algorithm was evaluated with digital mouse based simulations and a gastric cancer-bearing mouse based in situ experiment. Primary results demonstrated the feasibility and superiority of the proposed algorithm for the turbid medium with low- and non-scattering regions.

60 APPLIED LIFE SCIENCES↗

First-order convex feasibility algorithms for x-ray CT

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution-thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle-Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144 Degree-Sign . The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Determination of Refractive Indices of a Layered Medium under Pulsed Irradiation

Problems related to determination of refractive indices of layered strongly scattering biological media by means of an optical tomography are investigated. Methods of reconstruction of refractive indices of layers, which are based on the smoothness properties of the solution to the initial-boundary problem, are proposed within the framework of the nonstationary radiative-transfer model. The influence of the probe-pulse duration on the accuracy of recovery of the sought-for characteristics of the medium is investigated numerically.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum process tomography by 2D fluorescence spectroscopy

Reconstruction of the dynamics (quantum process tomography) of the single-exciton manifold in energy transfer systems is proposed here on the basis of two-dimensional fluorescence spectroscopy (2D-FS) with phase-modulation. The quantum-process-tomography protocol introduced here benefits from, e.g., the sensitivity enhancement ascribed to 2D-FS. Although the isotropically averaged spectroscopic signals depend on the quantum yield parameter Γ of the doubly excited-exciton manifold, it is shown that the reconstruction of the dynamics is insensitive to this parameter. Applications to foundational and applied problems, as well as further extensions, are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Field evaporation of ZnO: A first-principles study

With recent advances in atom probe tomography of insulators and semiconductors, there is a need to understand high electrostatic field effects in these materials as well as the details of field evaporation. We use density functional theory to study field effects in ZnO clusters calculating the potential energy curves, the local field distribution, the polarizability, and the dielectric constant as a function of field strength. We confirm that, as in MgO, the HOMO-LUMO gap of a ZnO cluster closes at the evaporation field strength signaling field-induced metallization of the insulator. Following the structural changes in the cluster at the evaporation field strength, we can identify the field evaporated species, in particular, we show that the most abundant ion, Zn{sup 2+}, is NOT post-ionized but leaves the surface as 2+ largely confirming the experimental observations. Our results also help to explain problems related to stoichiometry in the mass spectra measured in atom probe tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nonlinear photoacoustic spectroscopy of hemoglobin

As light intensity increases in photoacoustic imaging, the saturation of optical absorption and the temperature dependence of the thermal expansion coefficient result in a measurable nonlinear dependence of the photoacoustic (PA) signal on the excitation pulse fluence. Here, under controlled conditions, we investigate the intensity-dependent photoacoustic signals from oxygenated and deoxygenated hemoglobin at varied optical wavelengths and molecular concentrations. The wavelength and concentration dependencies of the nonlinear PA spectrum are found to be significantly greater in oxygenated hemoglobin than in deoxygenated hemoglobin. These effects are further influenced by the hemoglobin concentration. These nonlinear phenomena provide insights into applications of photoacoustics, such as measurements of average inter-molecular distances on a nm scale or with a tuned selection of wavelengths, a more accurate quantitative PA tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Compartment modeling of dynamic brain PET—The impact of scatter corrections on parameter errors

Purpose: The aim of this study was to investigate the effect of scatter and its correction on kinetic parameters in dynamic brain positron emission tomography (PET) tumor imaging. The 2-tissue compartment model was used, and two different reconstruction methods and two scatter correction (SC) schemes were investigated. Methods: The GATE Monte Carlo (MC) software was used to perform 2 × 15 full PET scan simulations of a voxelized head phantom with inserted tumor regions. The two sets of kinetic parameters of all tissues were chosen to represent the 2-tissue compartment model for the tracer 3′-deoxy-3′-({sup 18}F)fluorothymidine (FLT), and were denoted FLT{sub 1} and FLT{sub 2}. PET data were reconstructed with both 3D filtered back-projection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM). Images including true coincidences with attenuation correction (AC) and true+scattered coincidences with AC and with and without one of two applied SC schemes were reconstructed. Kinetic parameters were estimated by weighted nonlinear least squares fitting of image derived time–activity curves. Calculated parameters were compared to the true input to the MC simulations. Results: The relative parameter biases for scatter-eliminated data were 15%, 16%, 4%, 30%, 9%, and 7% (FLT{sub 1}) and 13%, 6%, 1%, 46%, 12%, and 8% (FLT{sub 2}) for K{sub 1}, k{sub 2}, k{sub 3}, k{sub 4}, V{sub a}, and K{sub i}, respectively. As expected, SC was essential for most parameters since omitting it increased biases by 10 percentage points on average. SC was not found necessary for the estimation of K{sub i} and k{sub 3}, however. There was no significant difference in parameter biases between the two investigated SC schemes or from parameter biases from scatter-eliminated PET data. Furthermore, neither 3DRP nor OSEM yielded the smallest parameter biases consistently although there was a slight favor for 3DRP which produced less biased k{sub 3} and K{sub i} estimates while OSEM resulted in a less biased V{sub a}. The uncertainty in OSEM parameters was about 26% (FLT{sub 1}) and 12% (FLT{sub 2}) larger than for 3DRP although identical postfilters were applied. Conclusions: SC was important for good parameter estimations. Both investigated SC schemes performed equally well on average and properly corrected for the scattered radiation, without introducing further bias. Furthermore, 3DRP was slightly favorable over OSEM in terms of kinetic parameter biases and SDs.

60 APPLIED LIFE SCIENCES↗

A fast algorithm for parabolic PDE-based inverse problems based on Laplace transforms and flexible Krylov solvers

We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in solving these inverse problems using Newton-type methods is the computational cost associated with solving the forward problem and with repeated construction of the Jacobian, which represents the sensitivity of the measurements to the unknown parameters. Forming the Jacobian can be prohibitively expensive because it requires repeated solutions of the forward and adjoint time-dependent parabolic partial differential equations corresponding to multiple sources and receivers. We propose an efficient method based on a Laplace transform-based exponential time integrator combined with a flexible Krylov subspace approach to solve the resulting shifted systems of equations efficiently. Our proposed solver speeds up the computation of the forward and adjoint problems, thus yielding significant speedup in total inversion time. We consider an application from Transient Hydraulic Tomography (THT), which is an imaging technique to estimate hydraulic parameters related to the subsurface from pressure measurements obtained by a series of pumping tests. The algorithms discussed are applied to a synthetic example taken from THT to demonstrate the resulting computational gains of this proposed method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimization of oncological {sup 18}F-FDG PET/CT imaging based on a multiparameter analysis

Purpose: This paper describes a method to achieve consistent clinical image quality in {sup 18}F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60–90 kg, >90 kg) allows improved image quality with both point spread function and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. Results: For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist’s top 2 ranked segments in 78.3% of the 254 groups (Cohen’s kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers’ top 2 rankings, and 96.5% agreed with at least one observer’s top 2 rankings. In comparison, agreement between the four observers’ top ranked segment and the radiologist’s top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. Conclusions: The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.

61 RADIATION PROTECTION AND DOSIMETRY↗

Poster — Thur Eve — 16: 4DCT simulation with synchronized contrast injection of liver SBRT patients

Stereotactic body radiation therapy (SBRT) has recently emerged as a valid option for treating liver metastases. SBRT delivers highly conformai dose over a small number of fractions. As such it is particularly sensitive to the accuracy of target volume delineation by the radiation oncologist. However, contouring liver metastases remains challenging for the following reasons. First, the liver usually undergoes significant motion due to respiration. Second, liver metastases are often nearly indistinguishable from the surrounding tissue when using computed tomography (CT) for imaging making it difficult to identify and delineate them. Both problems can be overcome by using four dimensional CT (4DCT) synchronized with intravenous contrast injection. We describe a novel CT simulation process which involves two 4DCT scans. The first scan captures the tumor and immediately surrounding tissue which in turn reduces the 4DCT scan time so that it can be optimally timed with intravenous contrast injection. The second 4DCT scan covers a larger volume and is used as the primary CT dataset for dose calculation, as well as patient setup verification on the treatment unit. The combination of two 4DCT scans, short and long, allows visualization of the liver metastases over all phases of breathing cycle while simultaneously acquiring long enough 4DCT dataset suitable for planning and patient setup verification.

60 APPLIED LIFE SCIENCES↗

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗

ALERT AATR Final Report: Lawrence Livermore National Laboratory

This report addresses the problem of automatically recognizing objects of interest (OOIs) in x-ray computed tomography (CT) images of baggage (plastic bins in our case). The discussion draws heavily from the material in [1]. The material composition and basic physical features of interest (FOIs, such as mass and thickness) of the OOIs are defined in an object requirement specification (ORS). The ORS may also provide a detection – false alarm probability goal for each material of interest (MOI). Automatic threat recognition (ATR) systems identify CT images of baggage that contain OOIs. ATRs must also identify locations of OOIs within baggage. The current ATR certification process used by DHS requires the ATR hardware and software to be certified on a specific ORS. When the ORS changes, the ATR hardware and software must be recertified. To pass re-certification, the hardware, algorithms and codes may need to be modified. Because ATR-based certification and re-certification are so time-consuming, the current process cannot quickly adapt to changing requirements. Unlike ATRs, adaptive automatic threat recognition (AATR) systems can quickly adapt to an ORS that changes or evolves over time [2]. The proposed AATR-based certification process would require the AATR hardware and software to be certified on a specific baseline ORS. Once certified, the same AATR hardware, algorithms and codes would be applied (by TSA or its delegates) to any ORS supplied in the future as input without going through lengthy recertification. This proposed process would enable the AATR to quickly adapt to changing requirements. This report describes the AATR developed at the Lawrence Livermore National Laboratory (LLNL) for x-ray CT images of baggage. 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/).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Efficient quantum state tomography with mode-assisted training

Neural networks (NNs) representing quantum states are typically trained using Markov chain Monte Carlo based methods. However, unless specifically designed, such samplers only consist of local moves, making the slow-mixing problem prominent even for extremely simple quantum states. Here, we propose to use mode-assisted training that provides global information via the modes of the NN distribution. Further, applied to quantum state tomography using restricted Boltzmann machines, this method improves the quality of reconstructed quantum states by orders of magnitude. The method is applicable to other types of NNs and may efficiently tackle problems previously unmanageable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cosmic shear results from the deep lens survey. II. Full cosmological parameter constraints from tomography

We present a tomographic cosmic shear study from the Deep Lens Survey (DLS), which, providing a limiting magnitude r{sub lim}∼27 (5σ), is designed as a precursor Large Synoptic Survey Telescope (LSST) survey with an emphasis on depth. Using five tomographic redshift bins, we study their auto- and cross-correlations to constrain cosmological parameters. We use a luminosity-dependent nonlinear model to account for the astrophysical systematics originating from intrinsic alignments of galaxy shapes. We find that the cosmological leverage of the DLS is among the highest among existing >10 deg{sup 2} cosmic shear surveys. Combining the DLS tomography with the 9 yr results of the Wilkinson Microwave Anisotropy Probe (WMAP9) gives Ω{sub m}=0.293{sub −0.014}{sup +0.012}, σ{sub 8}=0.833{sub −0.018}{sup +0.011}, H{sub 0}=68.6{sub −1.2}{sup +1.4} km s{sup −1} Mpc{sup −1}, and Ω{sub b}=0.0475±0.0012 for ΛCDM, reducing the uncertainties of the WMAP9-only constraints by ∼50%. When we do not assume flatness for ΛCDM, we obtain the curvature constraint Ω{sub k}=−0.010{sub −0.015}{sup +0.013} from the DLS+WMAP9 combination, which, however, is not well constrained when WMAP9 is used alone. The dark energy equation-of-state parameter w is tightly constrained when baryonic acoustic oscillation (BAO) data are added, yielding w=−1.02{sub −0.09}{sup +0.10} with the DLS+WMAP9+BAO joint probe. The addition of supernova constraints further tightens the parameter to w=−1.03±0.03. Our joint constraints are fully consistent with the final Planck results and also with the predictions of a ΛCDM universe.

79 ASTRONOMY AND ASTROPHYSICS↗

3D Experimental Measurements of Evolution of Force Chains in Natural Silica Sand

The mechanisms of force transmission in granular materials is a classic physics problem that has been addressed since the 19th century, when Heinrich Rudolf Hertz investigated the interaction between two similar objects that were in contact under compression. However, the study of force transmission mechanisms in assemblies of more particles has proven to be a formidable problem due to the complex nature of granular materials. In recent years, synchrotron microcomputed tomography (SMT) and three-dimensional X-ray diffraction microscopy (3DXRD) have been employed to study the mechanics of granular materials experimentally. Combining SMT and 3DXRD offers unique three-dimensional (3D) experimental measurements of the internal structure, kinematics (such as rotation and translation), and lattice strains of individual sand particles. In this paper, in situ SMT and 3DXRD scans were acquired at multiple load steps for a specimen composed of 2,705 natural Ottawa sand particles that were subjected to one-dimensional (1D) confined compression. An algorithm was developed to combine SMT images and 3DXRD lattice strain measurements and used to characterize the constitutive behavior of sand particles. The results were used to identify the crystal structure and the evolution of the stresses and lattice strains of individual sand particles. Another algorithm was developed to characterize the force structures within the specimen. Force structures were identified, and their properties (such as length) and evolution through the experiment were examined. The contact number of particles is a particle-scale property that affects the mechanics of granular materials. The effect of the contact number of the sand particles on the onset and evolution of the force structures was also investigated and discussed.

3D x-ray diffraction microscopy↗

Evaluation of the Feasibility of Utilizing a Low-Cost UWB Radar for Hardware Implant & Counterfeit Device Detection

Hardware implants & counterfeit devices in the US power grid pose a significant national security threat. Asset owners currently have few options for detecting the presence of such devices “in the wild”. The goal of this work is to develop a non-invasive sensing method to solve this problem. In this work we evaluate the feasibility of implementing a nonlinear UWB radar tomography system to differentiate between electronic internals of externally-similar devices using low-cost off-the-shelf hardware.

24 POWER TRANSMISSION AND DISTRIBUTION↗