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At least 199 records · Page 11

Initial Assessment of X-Ray Computer Tomography image analysis for material defect microstructure

The original development work leading to this report was focused on the non destructive three-dimensional (3-D) characterization of nuclear graphite as a means to better understand the nature of the inherent pore structure. The pore structure of graphite and its evolution under various environmental factors such as irradiation, mechanical stress, and oxidation plays an important role in their observed properties and characteristics. If we are to transition from an empirical understanding of graphite behavior to a truly predictive mechanistic understanding the pore structure must be well characterized and understood. As the pore structure within nuclear graphite is highly interconnected and truly 3-D in nature, 3-D characterization techniques are critical. While 3-D characterization has been an excellent tool for graphite pore characterization, it is applicable to a broad number of materials systems over many length scales. Given the wide range of applications and the highly quantitative nature of the tool, it is quite surprising to discover how few materials researchers understand and how valuable of a tool 3-D image processing and analysis can be. Ultimately, this report is intended to encourage broader use of 3 D image processing and analysis in materials science and engineering applications, more specifically nuclear-related materials applications, by providing interested readers with enough familiarity to explore its vast potential in identifying microstructure changes. To encourage this broader use, the report is divided into two main sections. Section 2 provides an overview of some of the key principals and concepts needed to extract a wide variety of quantitative metrics from a 3-D representation of a material microstructure. The discussion includes a brief overview of segmentation methods, connective components, morphological operations, distance transforms, and skeletonization. Section 3 focuses on the application of concepts from Section 2 to relevant materials at Idaho National Laboratory. In this section, image analysis examples featuring nuclear graphite will be discussed in detail. Additionally, example analyses from Transient Reactor Test Facility low-enriched uranium conversion, Advanced Gas Reactor like compacts, and tristructural isotopic particles are shown to give a broader perspective of the applicability to relevant materials of interest.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

On the possibility of a significant improvement in the quality of a quantum ghost image by registering an additional image in the object channel

A modification of the classical scheme of the quantum ghost image formation is considered, in which an image of the object under study is formed and recorded in the object channel. This image is used together with the ghost image to construct an estimate of the transparency distribution of the object. It is shown that this technique reduces the image quality worsening associated with the non-unit quantum efficiency of the sensors, even when the quantum image obtained in the object channel is additionally distorted by noise due to photons that did not interact with the object. (image processing)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DARHT Radiographic Grid Scale Correction

Recently it became apparent that the radiographic grid which has been used to calibrate the dimensional scale of DARHT radiographs was not centered at the location where the objects have been centered. This offset produced an error of 0.188% in the dimensional scaling of the radiographic images processed using the assumption that the grid and objects had the same center. This paper will show the derivation of the scaling correction, explain how new radiographs are being processed to account for the difference in location, and provide the details of how to correct radiographic image processed with the erroneous scale factor.

47 OTHER INSTRUMENTATION↗

Radiographic Magnification Differences Due To Grid Placement at DARHT

In 2015, it became apparent that the radiographic grid, which has been used to calibrate the dimensional scale of DARHT radiographs, was not centered at the location where the objects have been centered along the beamline. Instead of the grid center being placed at 133.0 cm, the grid downstream face was placed at this location, putting the grid center at 132.75 cm. This o set produced an error of 0.188% in the dimensional scaling of the radiographic images processed, using the assumption that the grid and objects had the same center. The Air Force Target (AFT) had the same holder as the grid, while the Circular Resolution Target (CRT) used a holder that correctly placed the object center at 133.0 cm. These erroneous holders were used until October 2015. Starting in November 2015, new holders were used that placed all static target objects in the correct location, with their center at 133.0 cm. This paper will show the derivation of the scaling correction, explain how old radiographs are being processed to account for the difference in location, and provide the details of how to correct radiographic images processed with the erroneous scale factor.

47 OTHER INSTRUMENTATION↗

Three-dimensional visualization and characterization of bone structure using reconstructed in-vitro μCT images: A pilot study for bone microarchitecture analysis

Micro Computed Tomography (μCT) has been largely used to perform micrometer scale imaging of specimens, bone biopsies and small animals for the study of porous or cavity-containing objects. One of its favored applications is for assessing structural properties of bone. In this research, we perform a pilot study to visualize and characterize bone structure of a chicken bone thigh, as well as to delineate its cortical and trabecular bone regions. We utilize an In-Vitro μCT scanner Skyscan 1173 to acquire a three dimensional image data of a chicken bone thigh. The thigh was scanned using X-ray voltage of 45 kV and current of 150 μA. The reconstructed images have spatial resolution of 142.50 μm/pixel. Using image processing and analysis e.i segmentation by thresholding the gray values (which represent the pseudo density) and binarizing the images, we were able to visualize each part of the bone, i.e., the cortical and trabecular regions. Total volume of the bone is 4663.63 mm{sup 3}, and the surface area of the bone is 7913.42 mm{sup 2}. The volume of the cortical is approximately 1988.62 mm{sup 3} which is nearly 42.64% of the total bone volume. This pilot study has confirmed that the μCT is capable of quantifying 3D bone structural properties and defining its regions separately. For further development, these results can be improved for understanding the pathophysiology of bone abnormality, testing the efficacy of pharmaceutical intervention, or estimating bone biomechanical properties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

AGR-2 TRISO Shadow Imaging Archive

As a part of fuel quality control characterization, backlit shadow images of particles produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-2 irradiation campaign were acquired at Oak Ridge National Laboratory (ORNL). These images may be of use for the development of image processing algorithms with the benchmark values measured at ORNL. This report provides those benchmark values, along with the raw images and data generated by the ORNL shadow imaging process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1

This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone. - Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building). - Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation. - Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.

Granderson, Jessica↗

Comprehensive experimental investigation on biomass-glass beads binary fluidization: A data set for CFD model validation

Fluidization behavior of biomass and glass beads binary mixtures in a bubbling fluidized bed was experimentally investigated. Mixtures containing different mass fraction of Loblolly Pine white wood and glass beads were fluidized at different fluidization velocities. The particle properties were characterized in a QICPIC that uses a dynamic image processing method to measure both particle size and sphericity. The minimum fluidization velocity was determined using the pressure drop method. An image processing method was developed to capture the dynamic expanded bed height at a very high frequency. The effect of biomass mass fraction and inlet gas velocity on mixing and segregation behavior was studied and analyzed through pressure drop measurements. Pressure drop fluctuations and expanded bed height fluctuations via fast Fourier transform were analyzed and compared. Here, the complete and accurate experimental data reported in this study could provide a benchmark data set for various computational fluid dynamics models validation, calibration, and identification.

42 ENGINEERING↗

Contour interpolated radial basis functions with spline boundary correction for fast 3D reconstruction of the human articular cartilage from MR images

Purpose: The aim of this work is to demonstrate a new image processing technique that can provide a “near real-time” 3D reconstruction of the articular cartilage of the human knee from MR images which is user friendly. This would serve as a point-of-care 3D visualization tool which would benefit a consultant radiologist in the visualization of the human articular cartilage. Methods: The authors introduce a novel fusion of an adaptation of the contour method known as “contour interpolation (CI)” with radial basis functions (RBFs) which they describe as “CI-RBFs.” The authors also present a spline boundary correction which further enhances volume estimation of the method. A subject cohort consisting of 17 right nonpathological knees (ten female and seven male) is assessed to validate the quality of the proposed method. The authors demonstrate how the CI-RBF method dramatically reduces the number of data points required for fitting an implicit surface to the entire cartilage, thus, significantly improving the speed of reconstruction over the comparable RBF reconstruction method of Carr. The authors compare the CI-RBF method volume estimation to a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Results: The authors demonstrate how the CI-RBF method significantly reduces the number of data points (p-value < 0.0001) required for fitting an implicit surface to the cartilage, by 48%, 31%, and 44% for the patellar, tibial, and femoral cartilages, respectively. Thus, significantly improving the speed of reconstruction (p-value < 0.0001) by 39%, 40%, and 44% for the patellar, tibial, and femoral cartilages over the comparable RBF model of Carr providing a near real-time reconstruction of 6.49, 8.88, and 9.43 min for the patellar, tibial, and femoral cartilages, respectively. In addition, it is demonstrated how the CI-RBF method matches the volume estimation of a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Furthermore, the performance of the segmentation method used for the extraction of the femoral, tibial, and patellar cartilages is assessed with a Dice similarity coefficient, sensitivity, and specificity measure providing high agreement to manual segmentation. Conclusions: The CI-RBF method provides a fast, accurate, and robust 3D model reconstruction that matches Carr’s RBF method, 3D DOCTOR, and a manual benchmark method in accuracy and significantly improves upon Carr’s RBF method in data requirement and computational speed. In addition, the visualization tool has been designed to quickly segment MR images requiring only four mouse clicks per MR image slice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SpIES: The Spitzer IRAC Equatorial Survey

We describe the first data release from the Spitzer-IRAC Equatorial Survey (SpIES); a large-area survey of ∼115 deg{sup 2} in the Equatorial SDSS Stripe 82 field using Spitzer during its “warm” mission phase. SpIES was designed to probe sufficient volume to perform measurements of quasar clustering and the luminosity function at z ⩾ 3 to test various models for “feedback” from active galactic nuclei (AGNs). Additionally, the wide range of available multi-wavelength, multi-epoch ancillary data enables SpIES to identify both high-redshift (z ⩾ 5) quasars as well as obscured quasars missed by optical surveys. SpIES achieves 5σ depths of 6.13 μJy (21.93 AB magnitude) and 5.75 μJy (22.0 AB magnitude) at 3.6 and 4.5 μm, respectively—depths significantly fainter than the Wide-field Infrared Survey Explorer (WISE). We show that the SpIES survey recovers a much larger fraction of spectroscopically confirmed quasars (∼98%) in Stripe 82 than are recovered by WISE (∼55%). This depth is especially powerful at high-redshift (z ⩾3.5), where SpIES recovers 94% of confirmed quasars, whereas WISE only recovers 25%. Here we define the SpIES survey parameters and describe the image processing, source extraction, and catalog production methods used to analyze the SpIES data. In addition to this survey paper, we release 234 images created by the SpIES team and three detection catalogs: a 3.6 μm only detection catalog containing ∼6.1 million sources, a 4.5 μm only detection catalog containing ∼6.5 million sources, and a dual-band detection catalog containing ∼5.4 million sources.

79 ASTRONOMY AND ASTROPHYSICS↗

The correlation study of parallel feature extractor and noise reduction approaches

This paper presents literature reviews that show variety of techniques to develop parallel feature extractor and finding its correlation with noise reduction approaches for low light intensity images. Low light intensity images are normally displayed as darker images and low contrast. Without proper handling techniques, those images regularly become evidences of misperception of objects and textures, the incapability to section them. The visual illusions regularly clues to disorientation, user fatigue, poor detection and classification performance of humans and computer algorithms. Noise reduction approaches (NR) therefore is an essential step for other image processing steps such as edge detection, image segmentation, image compression, etc. Parallel Feature Extractor (PFE) meant to capture visual contents of images involves partitioning images into segments, detecting image overlaps if any, and controlling distributed and redistributed segments to extract the features. Working on low light intensity images make the PFE face challenges and closely depend on the quality of its pre-processing steps. Some papers have suggested many well established NR as well as PFE strategies however only few resources have suggested or mentioned the correlation between them. This paper reviews best approaches of the NR and the PFE with detailed explanation on the suggested correlation. This finding may suggest relevant strategies of the PFE development. With the help of knowledge based reasoning, computational approaches and algorithms, we present the correlation study between the NR and the PFE that can be useful for the development and enhancement of other existing PFE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Real-time out-of-plane artifact subtraction tomosynthesis imaging using prior CT for scanning beam digital x-ray system

Purpose: The scanning beam digital x-ray system (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real-time tomosynthesis in multiple planes. This system could be used for image guidance during lung nodule biopsy. However, the reconstructed images suffer from strong out-of-plane artifact due to the small tomographic angle of the system. Methods: The authors propose an out-of-plane artifact subtraction tomosynthesis (OPAST) algorithm that utilizes a prior CT volume to augment the run-time image processing. A blur-and-add (BAA) analytical model, derived from the project-to-backproject physical model, permits the generation of tomosynthesis images that are a good approximation to the shift-and-add (SAA) reconstructed image. A computationally practical algorithm is proposed to simulate images and out-of-plane artifacts from patient-specific prior CT volumes using the BAA model. A 3D image registration algorithm to align the simulated and reconstructed images is described. The accuracy of the BAA analytical model and the OPAST algorithm was evaluated using three lung cancer patients’ CT data. The OPAST and image registration algorithms were also tested with added nonrigid respiratory motions. Results: Image similarity measurements, including the correlation coefficient, mean squared error, and structural similarity index, indicated that the BAA model is very accurate in simulating the SAA images from the prior CT for the SBDX system. The shift-variant effect of the BAA model can be ignored when the shifts between SBDX images and CT volumes are within ±10 mm in the x and y directions. The nodule visibility and depth resolution are improved by subtracting simulated artifacts from the reconstructions. The image registration and OPAST are robust in the presence of added respiratory motions. The dominant artifacts in the subtraction images are caused by the mismatches between the real object and the prior CT volume. Conclusions: Their proposed prior CT-augmented OPAST reconstruction algorithm improves lung nodule visibility and depth resolution for the SBDX system.

60 APPLIED LIFE SCIENCES↗

Non-Destructive, Three-Dimensional Imaging of Processes in the Rhizosphere Utilizing High Energy Photons

Soil structure, which can be described as the aggregation and distribution of pore spaces, regulates carbon, nutrient, and water cycling across the Earth system. Yet the inability to make quantitative, dynamic, in situ measurements of soil structure and rhizosphere carbon flow has prevented meaningful incorporation of soil structural processes into Earth System Models (ESMs). The key limitations are: (i) Lack of scale integration between micron-scale soil structure and ecosystem-scale models, (ii) Poor functional linkage between soil structural properties and biogeochemical processes, and (iii) Absence of dynamic 3D measurements of rhizosphere structural changes and carbon transformations. To address these challenges, we developed a new integrated positron emission tomography (PET) - microcomputed tomography (CT) imaging platform that enables the first 4D (spatial 3D and time), non-invasive, quantitative imaging of carbon allocation and rhizosphere structural dynamics in living plants and intact soils. The system combines: • Rhizo-PET (R-PET): a high-resolution positron emission tomography scanner optimized for 11 CO 2 tracing in plant roots. • a-Se micro-CT: a high-contrast, high-spatial resolution CT system based on amorphous selenium (a-Se) direct conversion technology, enabling micron-scale visualization of soil structure and root–soil interfaces. Together, these advances allow us to quantify how carbon exudates move, transform, and stabilize within the rhizosphere, directly informing missing processes in BER-relevant carbon cycle models.

42 ENGINEERING↗

A Method to Recognize Anatomical Site and Image Acquisition View in X-ray Images

A method was developed to recognize anatomical site and image acquisition view automatically in 2D X-ray images that are used in image-guided radiation therapy. The purpose is to enable site and view dependent automation and optimization in the image processing tasks including 2D-2D image registration, 2D image contrast enhancement, and independent treatment site confirmation. The X-ray images for 180 patients of six disease sites (the brain, head-neck, breast, lung, abdomen, and pelvis) were included in this study with 30 patients each site and two images of orthogonal views each patient. A hierarchical multiclass recognition model was developed to recognize general site first and then specific site. Each node of the hierarchical model recognized the images using a feature extraction step based on principal component analysis followed by a binary classification step based on support vector machine. Given two images in known orthogonal views, the site recognition model achieved a 99% average F1 score across the six sites. If the views were unknown in the images, the average F1 score was 97%. If only one image was taken either with or without view information, the average F1 score was 94%. The accuracy of the site-specific view recognition models was 100%.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Technical Note: Impact on detective quantum efficiency of edge angle determination method by International Electrotechnical Commission methodology for cardiac x-ray image detectors

Purpose: Cardiac x-ray detectors are used to acquire moving images in real-time for angiography and interventional procedures. Detective quantum efficiency (DQE) is not generally measured on these dynamic detectors; the required “for processing” image data and control of x-ray settings have not been accessible. By 2016, USA hospital physicists will have the ability to measure DQE and will likely utilize the International Electrotechnical Commission (IEC) standard for measuring DQE of dynamic x-ray imaging devices. The current IEC standard requires an image of a tilted tungsten edge test object to obtain modulation transfer function (MTF) for DQE calculation. It specifies the range of edge angles to use; however, it does not specify a preferred method to determine this angle for image analysis. The study aimed to answer the question “will my choice in method impact my results?” Four different established edge angle determination methods were compared to investigate the impact on DQE. Methods: Following the IEC standard, edge and flat field images were acquired on a cardiac flat-panel detector to calculate MTF and noise power spectrum, respectively, to determine DQE. Accuracy of the methods in determining the correct angle was ascertained using a simulated edge image with known angulations. Precision of the methods was ascertained using variability of MTF and DQE, calculated via bootstrapping. Results: Three methods provided near equal angles and the same MTF while the fourth, with an angular difference of 6%, had a MTF lower by 3% at 1.5 mm{sup −1} spatial frequency and 8% at 2.5 mm{sup −1}; corresponding DQE differences were 6% at 1.5 mm{sup −1} and 17% at 2.5 mm{sup −1}; differences were greater than standard deviations in the measurements. Conclusions: DQE measurements may vary by a significant amount, depending on the method used to determine the edge angle when following the IEC standard methodology for a cardiac x-ray detector. The most accurate and precise methods are recommended for absolute assessments and reproducible measurements, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Predicting Switchgrass Biomass Yields Using a Spectral Vegetation Index Derived from Multispectral Satellite Imagery

Successful scaling of perennial bioenergy crop production requires a landscape design that optimizes the benefits of finite lands for people, communities, and environments. Utilizing marginal areas is the key to sustainable bioenergy crop production (Ssegane et al., 2015, 2016). Marginal areas are often small-sized lands and unevenly distributed across the agricultural landscape (Ssegane et al., 2016); thus, a systematic, semi-automated remote sensing method is needed as an effective means of estimating bioenergy crop yields across landscapes. Argonne National Laboratory (Argonne) is currently developing a tool, Scaling Up Perennial Bioenergy Economics and Ecosystem Services Tool (SUPERBEEST), to identify marginal agricultural lands and quantify environmental and economic effects of perennial bioenergy crop production systems. The tool aims to provide users a path to foster the sustainable and productive integration of bioenergy crops in the Midwestern agricultural landscape. Reliable, cost-effective, and timely estimation of bioenergy crop yields using remote sensing would help calculate and track the success of integrated bioenergy crops in the landscape for those communities. Argonne previously conducted feasibility studies for estimating biomass yields for bioenergy feedstock, corn and perennial grass using spectral vegetation indices (SVIs)1 derived from optical imagery (Hamada et al., 2015, 2021). In both studies, SVIs, more specifically those sensitive to plant chlorophyll or nitrogen contents, showed potential for estimating or predicting biomass yields with a correlation of determination (R2) ranging from 0.54 to 0.96, indicating a value for further investigation as a viable means of quantifying bioenergy feedstock production across large landscapes. Thus, the goal of this study is to evaluate the feasibility of use of SVIs as a means of estimating or predicting switchgrass biomass yields at harvest using publicly available multispectral satellite imagery. The feasibility analysis was performed using four study areas of mature switchgrass located in Virginia. Objectives are to (1) examine the SVIs and establish their relationships with switchgrass biomass yields at harvest, (2) develop a parsimonious image processing model for predicting at-harvest yields by applying the relationships with the most promising spectral index and (3) map switchgrass yields predicted by the image processing model across the study sites. The calibration to field data will rely on switchgrass biomass yields determined by the baling method, representing a potential challenge to the analysis but an important practical aspect for future applications. With this research design, the study aimed to gain insights into enabling remote sensing-based estimation of bioenergy crop yields in a reliable, cost- effective, and timely manner across large, heterogeneous landscapes.

09 BIOMASS FUELS↗

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗

Revealing asymmetries in the HD 181327 debris disk: A recent massive collision or interstellar medium warping

New multi-roll coronagraphic images of the HD 181327 debris disk obtained using the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope reveal the debris ring in its entirety at high signal-to-noise ratio and unprecedented spatial resolution. We present and apply a new multi-roll image processing routine to identify and further remove quasi-static point-spread function-subtraction residuals and quantify systematic uncertainties. We also use a new iterative image deprojection technique to constrain the true disk geometry and aggressively remove any surface brightness asymmetries that can be explained without invoking dust density enhancements/deficits. The measured empirical scattering phase function for the disk is more forward scattering than previously thought and is not well-fit by a Henyey-Greenstein function. The empirical scattering phase function varies with stellocentric distance, consistent with the expected radiation pressured-induced size segregation exterior to the belt. Within the belt, the empirical scattering phase function contradicts unperturbed debris ring models, suggesting the presence of an unseen planet. The radial profile of the flux density is degenerate with a radially varying scattering phase function; therefore estimates of the ring's true width and edge slope may be highly uncertain. We detect large scale asymmetries in the disk, consistent with either the recent catastrophic disruption of a body with mass >1% the mass of Pluto, or disk warping due to strong interactions with the interstellar medium.

79 ASTRONOMY AND ASTROPHYSICS↗