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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Closed-Form Approximation of the Total Variation Proximal Operator

Total variation (TV) is a widely used function for regularizing imaging inverse problems that is particularly appropriate for images whose underlying structure is piecewise constant. TV regularized optimization problems are typically solved using proximal methods, but the way in which they are applied is constrained by the absence of a closed-form expression for the proximal operator of the TV function. A closed-form approximation of the TV proximal operator has previously been proposed, but its accuracy was not theoretically explored in detail. Here, we address this gap by making several new theoretical contributions, proving that the approximation leads to a proximal operator of some convex function, it is equivalent to a gradient descent step on a smoothed version of TV, and that its error can be fully characterized and controlled with its scaling parameter. We experimentally validate our theoretical results on image denoising and sparse-view computed tomography (CT) image reconstruction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm{sup 2} field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical measurements were 0.97 ± 0.03 and 1.10 ± 0.13, respectively, indicating that the accuracy of the Monte Carlo simulation was adequate. The normalized AGD with VOI field scans was substantially reduced by a factor of about 2 over the VOI region and by a factor of 18 over the entire breast for both 25% and 50% VGF simulated breasts compared with the normalized AGD with full field scans. The normalized AGD for the VOI breast CT technique can be kept the same as or lower than that for a full field scan with the exposure level for the VOI field scan increased by a factor of as much as 12. Conclusions: The authors’ Monte Carlo estimates of normalized AGDs for the VOI breast CT technique show that this technique can be used to markedly increase the dose to the breast and thus the visibility of the VOI region without increasing the dose to the breast. The results of this investigation should be helpful for those interested in using VOI breast CT technique to image small calcifications with dose concern.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

In-situ 4D visualization and analysis of temperature-driven creep in an oil shale propped fracture

Here, the proppant embedment due to creep in shales is a known issue affecting the useable lifetime of wells in unconventional oil and gas recovery. One of the factors influencing creep is the presence of organics, whose properties can be very sensitive to temperature. In this work we investigated for the first time the role of temperature-induced creep increase in proppant embedment in an organics-rich Green River oil shale sample via in-situ synchrotron X-ray micro-computed tomography. We observed that temperatures as low as 75 °C already induce fast creep, with a fracture aperture closing rate of 13 μm/h and a loss of fracture conductivity rate of 8.7%/h, due only to proppant embedment, in the measured interval at the first heating stage. Local displacement data analysis provided evidence for markedly plastic deformation around the proppant-shale contacts, in contrast with the brittle proppant embedment observed on more cemented and less organics-rich shales at room temperature. The results highlight how the problem of temperature-dependent mechanical behavior might be more important than previously thought, in shales with a high content in organics, and that in-situ micro-imaging techniques can play a key role in understanding the underlying mechanisms, contributing to solve creep-related problems associated with hydraulic fracturing in complex scenarios.

02 PETROLEUM↗
DOE OSTI2015

On the interplay between relaxation, defect formation, and atomic Sn distribution in Ge{sub (1−x)}Sn{sub (x)} unraveled with atom probe tomography

Ge{sub (1−x)}Sn{sub (x)} has received a lot of interest for opto-electronic applications and for strain engineering in advanced complementary-metal-oxide-semiconductor technology, because it enables engineering of the band gap and inducing strain in the alloy. To target a reliable technology for mass application in microelectronic devices, the physical problem to be addressed is to unravel the complex relationship between strain relaxation (as induced by the growth of large layer thicknesses or a thermal anneal) and defect formation, and/or stable Sn-cluster formation. In this paper, we study the onset of Sn-cluster formation and its link to strain relaxation using Atom Probe Tomography (APT). To this end, we also propose a modification of the core-linkage [Stephenson et al., Microsc. Microanal. 13, 448 (2007)] cluster analysis method, to overcome the challenges of limited detection efficiency and lateral resolution of APT, and the quantitative assessment for very small clusters (<40 atoms) embedded in a random distribution of Sn-atoms. We concluded that the main relaxation mechanism for these layers is defect generation (misfit dislocations, threading dislocations, etc.), irrespective of the cause (thickness of layer or thermal anneal) of relaxation and is independent of the cluster formation. The low thermodynamic solubility limit of Sn in Ge seems to be the driving force for Sn-cluster formation. Finally, we also discuss the spatial distribution of Sn in clusters and relate them to the theoretically predicted stable Sn clusters [Ventura et al., Phys. Rev. B 79, 155202 (2009)].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Fast and noise-tolerant determination of the center of rotation in tomography

High-quality tomographic reconstruction is not possible without the accurate localization of the center of rotation. Poor localization leads to artifacts in the data and can even cause reconstructions to fail. There are many approaches to solving this problem, some of which involve the collection of full sinograms, or even provisional tomographic reconstructions, in order to determine the center of rotation. Here, a simple method based on the expected symmetry of the Fourier transform of summed projections approximately 180° apart is presented; unlike cross-correlation methods, it requires only a single Fourier transform to compute, and uses mainly low spatial frequency information which is less susceptible to noise. This approach is shown to be fast, and robust against poor signal-to-noise as well as to projection images acquired at angles that are not exactly 180° apart. This rapid method can be useful as a first step in the processing of tomographic data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties

Abstract Motivation BISCAP is a state-of-the-art tool for automatically characterizing biofilm images obtained from Optical Coherence Tomography. Limited availability of other software tools is reported in the field. BISCAP’s first version processes 2D images only. Processing 3D images is a problem of greater scientific relevance since it deals with the entire structure of biofilms instead of their 2D slices. Results Building on the image-processing principles and algorithms proposed earlier for 2D images, these were adapted to the 3D case, and a more general implementation of BISCAP was developed. The primary goal concerns the extension of the initial methodology to incorporate the depth axis in 3D images; multiple improvements were also made to boost computational performance. The calculation of structural properties and visual outputs was extended to offer new insights into the 3D structure of biofilms. BISCAP was tested using 3D images of biofilms with different morphologies, consistently delivering accurate characterizations of 3D structures in a few minutes using standard laptop machines. Low user dependency is required for image analysis. Availability and implementation BISCAP is available from https://github.com/diogonarciso/BISCAP. All images used in the tutorials and the validation examples are available from https://web.fe.up.pt/∼fgm/biscap3d.

Narciso, Diogo A. C. (ORCID:0000000227767477)↗
DOE OSTI2020

Nanoscale x-ray and electron tomography

We present that three-dimensional (3D) tomographic imaging of the structural, chemical, and physical properties of a material provides key knowledge that links the structure of a material to both its processing and structure that is central to studies across a broad spectrum of materials. For many decades, tomography using x-rays or electrons has proven to be an essential 3D characterization tool. In recent years, advances in technology have significantly pushed the envelope of these techniques in many respects, enabling new imaging capabilities at the nanometer and atomic scale. This article highlights several such developments in nanoscale x-ray and electron tomography. The five articles that appear in this issue of MRS Bulletin discuss research frontiers that include multimodal x-ray tomography at the nanoscale, x-ray spectroscopic tomography, dark-field x-ray microscopy, electron nanotomography for functional nanomaterials, and atomistic imaging by electron tomography. Lastly, these articles give a holistic view of the status of these techniques and promising future directions, as well highlighting their applications for scientific problems.

36 MATERIALS SCIENCE↗
DOE OSTI2011

An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography

Purpose: Bioluminescence tomography (BLT) provides an effective tool for monitoring physiological and pathological activities in vivo. However, the measured data in bioluminescence imaging are corrupted by noise. Therefore, regularization methods are commonly used to find a regularized solution. Nevertheless, for the quality of the reconstructed bioluminescent source obtained by regularization methods, the choice of the regularization parameters is crucial. To date, the selection of regularization parameters remains challenging. With regards to the above problems, the authors proposed a BLT reconstruction algorithm with an adaptive parameter choice rule. Methods: The proposed reconstruction algorithm uses a diffusion equation for modeling the bioluminescent photon transport. The diffusion equation is solved with a finite element method. Computed tomography (CT) images provide anatomical information regarding the geometry of the small animal and its internal organs. To reduce the ill-posedness of BLT, spectral information and the optimal permissible source region are employed. Then, the relationship between the unknown source distribution and multiview and multispectral boundary measurements is established based on the finite element method and the optimal permissible source region. Since the measured data are noisy, the BLT reconstruction is formulated as l{sub 2} data fidelity and a general regularization term. When choosing the regularization parameters for BLT, an efficient model function approach is proposed, which does not require knowledge of the noise level. This approach only requests the computation of the residual and regularized solution norm. With this knowledge, we construct the model function to approximate the objective function, and the regularization parameter is updated iteratively. Results: First, the micro-CT based mouse phantom was used for simulation verification. Simulation experiments were used to illustrate why multispectral data were used rather than monochromatic data. Furthermore, the study conducted using an adaptive regularization parameter demonstrated our ability to accurately localize the bioluminescent source. With the adaptively estimated regularization parameter, the reconstructed center position of the source was (20.37, 31.05, 12.95) mm, and the distance to the real source was 0.63 mm. The results of the dual-source experiments further showed that our algorithm could localize the bioluminescent sources accurately. The authors then presented experimental evidence that the proposed algorithm exhibited its calculated efficiency over the heuristic method. The effectiveness of the new algorithm was also confirmed by comparing it with the L-curve method. Furthermore, various initial speculations regarding the regularization parameter were used to illustrate the convergence of our algorithm. Finally, in vivo mouse experiment further illustrates the effectiveness of the proposed algorithm. Conclusions: Utilizing numerical, physical phantom and in vivo examples, we demonstrated that the bioluminescent sources could be reconstructed accurately with automatic regularization parameters. The proposed algorithm exhibited superior performance than both the heuristic regularization parameter choice method and L-curve method based on the computational speed and localization error.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging: Theory, algorithms, and applications

Plug-and-play (PnP) priors constitute one of the most widely used frameworks for solving computational imaging problems through the integration of physical models and learned models. PnP leverages high-fidelity physical sensor models and powerful machine learning methods for prior modeling of data to provide state-of-the-art reconstruction algorithms. PnP algorithms alternate between minimizing a data fidelity term to promote data consistency and imposing a learned regularizer in the form of an image denoiser. Recent highly successful applications of PnP algorithms include biomicroscopy, computerized tomography (CT), magnetic resonance imaging (MRI), and joint ptychotomography. This article presents a unified and principled review of PnP by tracing its roots, describing its major variations, summarizing main results, and discussing applications in computational imaging. Additionally, we also point the way toward further developments by discussing recent results on equilibrium equations that formulate the problem associated with PnP algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Fishbone activity in experimental advanced superconducting tokamak neutral beam injection plasma

Repetitive fishbones near the trapped ion procession frequency were observed for the first time in the neutral beam injection high confinement plasmas in Experimental Advanced Superconducting Tokamak (EAST) tokamak, and diagnosed using a solid-state neutral particle analyzer based on a compact silicon photodiode together with an upgraded high spatial-temporal-resolution multi-arrays soft X-ray (SX) system. This 1/1 typical internal kink mode propagates in the ion-diamagnetism direction with a rotation speed faster than the bulk plasma in the plasma frame. From the SX measurements, this mode frequency is typical of chirping down and the energetic particle effect related to the twisting mode structure. This ion fishbone was found able to trigger a multiple core sawtooth crashes with edge-2/1 sideband modes, as well as to lead to a transition from fishbone to long lived saturated kink mode to fishbone. Furthermore, using SX tomography, a correlation between mode amplitude and mode frequency was found. Finally, a phenomenological prey–predator model was found to reproduce the fishbone nonlinear process well.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Non parametric denoising methods based on wavelets: Application to electron microscopy images in low exposure time

The 3D reconstruction of the Cryo-Transmission Electron Microscopy (Cryo-TEM) and Energy Filtering TEM images (EFTEM) hampered by the noisy nature of these images, so that their alignment becomes so difficult. This noise refers to the collision between the frozen hydrated biological samples and the electrons beam, where the specimen is exposed to the radiation with a high exposure time. This sensitivity to the electrons beam led specialists to obtain the specimen projection images at very low exposure time, which resulting the emergence of a new problem, an extremely low signal-to-noise ratio (SNR). This paper investigates the problem of TEM images denoising when they are acquired at very low exposure time. So, our main objective is to enhance the quality of TEM images to improve the alignment process which will in turn improve the three dimensional tomography reconstructions. We have done multiple tests on special TEM images acquired at different exposure time 0.5s, 0.2s, 0.1s and 1s (i.e. with different values of SNR)) and equipped by Golding beads for helping us in the assessment step. We herein, propose a structure to combine multiple noisy copies of the TEM images. The structure is based on four different denoising methods, to combine the multiple noisy TEM images copies. Namely, the four different methods are Soft, the Hard as Wavelet-Thresholding methods, Bilateral Filter as a non-linear technique able to maintain the edges neatly, and the Bayesian approach in the wavelet domain, in which context modeling is used to estimate the parameter for each coefficient. To ensure getting a high signal-to-noise ratio, we have guaranteed that we are using the appropriate wavelet family at the appropriate level. So we have chosen âĂIJsym8âĂİ wavelet at level 3 as the most appropriate parameter. Whereas, for the bilateral filtering many tests are done in order to determine the proper filter parameters represented by the size of the filter, the range parameter and the spatial parameter respectively. The experiments reported in this paper demonstrate the performance of the Bilateral Filtering and the Bayesian approaches in terms of improving the SNRout and the image quality. Taken together, these results suggest that the Bayesian process has a potential to outperform all the used methods, where in the multiple noisy copies structure it gave us the best SNRout without change of the golden beads diameter. The Bayesian approach yielded enhanced average image without needing a huge amount of copies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SU-G-IeP4-03: Cone Beam X-Ray Luminescence Computed Tomography Based On Generalized Gaussian Markov Random Field

Purpose: Cone beam X-ray luminescence computed tomography (CB-XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. However, the inverse problem of CB-XLCT is seriously ill-conditioned, hindering us to achieve good image quality. In this work, a novel reconstruction method based on Bayesian theory is proposed to tackle this problem Methods: Bayesian theory provides a natural framework for utilizing various kinds of available prior information to improve the reconstruction image quality. A generalized Gaussian Markov random field (GGMRF) model is proposed here to construct the prior model of the Bayesian theory. The most important feature of GGMRF model is the adjustable shape parameter p, which can be continuously adjusted from 1 to 2. The reconstruction image tends to have more edge-preserving property when p is slide to 1, while having more noise tolerance property when p is slide to 2, just like the behavior of L1 and L2 regularization methods, respectively. The proposed method provides a flexible regularization framework to adapt to a wide range of applications. Results: Numerical simulations were implemented to test the performance of the proposed method. The Digimouse atlas were employed to construct a three-dimensional mouse model, and two small cylinders were placed inside to serve as the targets. Reconstruction results show that the proposed method tends to obtain better spatial resolution with a smaller shape parameter, while better signal-to-noise image with a larger shape parameter. Quantitative indexes, contrast-to-noise ratio (CNR) and full-width at half-maximum (FWHM), were used to assess the performance of the proposed method, and confirmed its effectiveness in CB-XLCT reconstruction. Conclusion: A novel reconstruction method for CB-XLCT is proposed based on GGMRF model, which enables an adjustable performance tradeoff between L1 and L2 regularization methods. Numerical simulations were conducted to demonstrate its performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-207B-02: Material Reconstruction for Spectral Computed Tomography with Detector Response Function

Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelity based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Polarization Tomography of Residual Stresses in Cylindrical Gradient-Index Lenses

In most cases, cylindrical structures with a gradient refractive index (GRIN) are formed on the basis of diffusion technology. The refractive index and the residual stresses in them are axially symmetrical. The distortion determined by diffusion and the thermal internal stresses in them are simulated by the fictive temperature of residual stresses. The use of the integral photoelasticity for the reconstruction of residual stresses in GRIN lenses is usually limited to the case of a planar deformed state. In this study, this algorithm is extended to the case of the axial change of residual stresses. It is assumed that the illumination procedure is carried out in the sample cross section. The optical problem is solved within the quasi-isotropic approximation. The reconstruction is based on measuring the characteristic parameters of polarized light passed through the sample and on the combined solution of the thermoelasticity problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Quantitative cone beam X-ray luminescence tomography/X-ray computed tomography imaging

X-ray luminescence tomography (XLT) is an imaging technology based on X-ray-excitable materials. The main purpose of this paper is to obtain quantitative luminescence concentration using the structural information of the X-ray computed tomography (XCT) in the hybrid cone beam XLT/XCT system. A multi-wavelength luminescence cone beam XLT method with the structural a priori information is presented to relieve the severe ill-posedness problem in the cone beam XLT. The nanophosphors and phantom experiments were undertaken to access the linear relationship of the system response. Then, an in vivo mouse experiment was conducted. The in vivo experimental results show that the recovered concentration error as low as 6.67% with the location error of 0.85 mm can be achieved. The results demonstrate that the proposed method can accurately recover the nanophosphor inclusion and realize the quantitative imaging.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

A pencil beam approach to proton computed tomography

Purpose: A new approach to proton computed tomography (pCT) is presented. In this approach, protons are not tracked one-by-one but a beam of particles is considered instead. The elements of the pCT reconstruction problem (residual energy and path) are redefined on the basis of this new approach. An analytical image reconstruction algorithm applicable to this scenario is also proposed. Methods: The pencil beam (PB) and its propagation in matter were modeled by making use of the generalization of the Fermi–Eyges theory to account for multiple Coulomb scattering (MCS). This model was integrated into the pCT reconstruction problem, allowing the definition of the mean beam path concept similar to the most likely path (MLP) used in the single-particle approach. A numerical validation of the model was performed. The algorithm of filtered backprojection along MLPs was adapted to the beam-by-beam approach. The acquisition of a perfect proton scan was simulated and the data were used to reconstruct images of the relative stopping power of the phantom with the single-proton and beam-by-beam approaches. The resulting images were compared in a qualitative way. Results: The parameters of the modeled PB (mean and spread) were compared to Monte Carlo results in order to validate the model. For a water target, good agreement was found for the mean value of the distributions. As far as the spread is concerned, depth-dependent discrepancies as large as 2%–3% were found. For a heterogeneous phantom, discrepancies in the distribution spread ranged from 6% to 8%. The image reconstructed with the beam-by-beam approach showed a high level of noise compared to the one reconstructed with the classical approach. Conclusions: The PB approach to proton imaging may allow technical challenges imposed by the current proton-by-proton method to be overcome. In this framework, an analytical algorithm is proposed. Further work will involve a detailed study of the performances and limitations of this approach in terms of image quality. The paper shows how to account for the MCS in the reconstruction step with this new approach when an analytical reconstruction algorithm is used.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Three-dimensional tomographic imaging for dynamic radiation behavior study using infrared imaging video bolometers in large helical device plasma

A three-dimensional (3D) tomography system using four InfraRed imaging Video Bolometers (IRVBs) has been designed with a helical periodicity assumption for the purpose of plasma radiation measurement in the large helical device. For the spatial inversion of large sized arrays, the system has been numerically and experimentally examined using the Tikhonov regularization with the criterion of minimum generalized cross validation, which is the standard solver of inverse problems. The 3D transport code EMC3-EIRENE for impurity behavior and related radiation has been used to produce phantoms for numerical tests, and the relative calibration of the IRVB images has been carried out with a simple function model of the decaying plasma in a radiation collapse. The tomography system can respond to temporal changes in the plasma profile and identify the 3D dynamic behavior of radiation, such as the radiation enhancement that starts from the inboard side of the torus, during the radiation collapse. The reconstruction results are also consistent with the output signals of a resistive bolometer. These results indicate that the designed 3D tomography system is available for the 3D imaging of radiation. The first 3D direct tomographic measurement of a magnetically confined plasma has been achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗