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DOE OSTI2022

Data Mining – Image Analysis of Radiography for Zr Redistribution

The research effort described in this report represents a first attempt to investigate the radial redistribution of Zr in ternary fuel alloys U-xPu-10Zr (x = 0, 8, 19) irradiated in the in-reactor fuel experiments during the operation of the U.S. Department of Energy’s (DOE’s) Experimental Breeder Reactor II (EBR-II) at Idaho National Laboratory (INL) using methods of image processing on post-irradiation neutron radiographs. Approximately 130,000 metal fuel pins were irradiated in EBR-II during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed historically now allowing application of modern image analysis techniques to characterize fuel behavior, such as fuel swelling, fluff formation, and now, fuel alloy constituent redistribution. The redistribution of fuel components depends on the temperature field, radially, within the fuel. Specifically, Zr is expected to redistribute radially towards the center of the pin, as well as towards the outer zones. Currently, direct imaging of a pin cross-section through optical methods or scanning electron microscopy (SEM) is used to study the constituents’ redistribution, which is very time-consuming and can only be applied to a limited number of pins. An automated image processing technique allowing for the investigation of fuel radial redistribution zones would significantly accelerate data analysis. In general, if the fuel temperature is hot enough, three redistribution zones are expected, corresponding to the main fuel components (e.g., U, Pu, Zr). While more assessment will be performed in fiscal year (FY)-2023, it seems possible to differentiate the pins according to their fuel composition using image analysis techniques on neutron radiographs of metallic fuel pins based on the analysis to date.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

System-Independent X-Ray Characterization

We have developed a method for image reconstruction and analysis of dual-energy X-ray scans that has been demonstrated to yield a physically intuitive characterization of materials (by electron density and effective atomic number) in a system-independent way. Our methodology stands in contrast to common practice of reconstructing images to yield linear attenuation coefficients, which depend strongly on system spectral response. At the core of our method, a technique called dual-energy decomposition is used to generate spectral energy-independent characterizations of the attenuation properties of a material. Inputs to this decomposition include system spectral response estimates and dual-energy X-ray projection data. X-ray cross-section tables are used to convert decomposition results to physical feature estimates (electron density, effective atomic number). Our method currently works best for materials with atomic numbers below 22 (titanium). In prior work for DHS, we demonstrated in a controlled, no-clutter environment that the decomposition technique could be applied to scans of a well-characterized materials on multiple systems with different X-ray spectral responses. In cases where LAC values showed a standard deviation of as much as 20% of mean value, application of our method yielded results with standard deviations as low as 1–3% of mean value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗

NASA NTRS1999

Spectral Gradients and u-v Sampling

I describe a systematic method for characterizing the effects of differences in u-v coverage in terms of inferred spectral gradients in interferometric images. This method is directly applicable to optical and radio interferometry; it is useful in situations when observations using scale arrays are not feasible.

u-v sampling spectral gradients interferometric im↗

DOE OSTI2016

Imaging latex–carbon nanotube composites by subsurface electrostatic force microscopy

Electrostatic modes of atomic force microscopy have shown to be non-destructive and relatively simple methods for imaging conductors embedded in insulating polymers. Here we use electrostatic force microscopy to image the dispersion of carbon nanotubes in a latex-based conductive composite, which brings forth features not observed in previously studied systems employing linear polymer films. A fixed-potential model of the probe-nanotube electrostatics is presented which in principle gives access to the conductive nanoparticle's depth and radius, and the polymer film dielectric constant. Comparing this model to the data results in nanotube depths that appear to be slightly above the film–air interface. Furthermore, this result suggests that water-mediated charge build-up at the film–air interface may be the source of electrostatic phase contrast in ambient conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Utilizing fluorescent life time imaging microscopy technology for identify carriers of BRCA2 mutation

Worldwide, more than one million women are diagnosed with breast cancer every year, making it the most common female malignancy in the developed world. Germline mutations in BRCA1 and BRCA2 genes are estimated to increase the risk for developing breast cancer by up to 87%. From a clinical point of view, identification of BRCA1 and BRCA2 mutation carriers offers an opportunity to early identify or prevent the development of malignancy; therefore the ability to determine which women are more likely to carry BRCA1 or BRCA2 mutations is of great importance. The available diagnostic tests for mutation analysis of BRCA1 and BRCA2 are time- and labor-intensive, expensive, and do not allow the identification of all the functional mutations. We utilized the Fluorescent lifetime (FLT) imaging microscopy method which allows recognizing different cell populations, in order to distinguish between lymphocytes from BRCA1 and BRCA2 mutation carriers and non-carrier women by using easily obtainable lymphocyte cells from peripheral blood. Our results demonstrate that cells originated from BRCA2-mutation carriers have significantly lower FLT values compared with BRCA1 mutation carriers and control cells. This simple, inexpensive and sensitive method may be utilized in the future to detect BRCA2 mutation carriers, particularly those bearing unknown functional mutations. - Highlights: • Fluorescent lifetime imaging microscopy (FLIM) technology can be used for recognizing BRCA mutation carriers. • Cells originated from BRCA2-mutation carriers have lower FLT values compared with BRCA1 mutation carriers and control cells. • The difference in FLT values were observed regardless irradiation. • FLIM method may be more informative in the detection of BRCA2-mutation carriers than BRCA1.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2016

Normalized Temperature Contrast Processing in Infrared Flash Thermography

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

Koshti, Ajay M.↗

NASA NTRS2016

A Method to Measure and Estimate Normalized Contrast in Infrared Flash Thermography

Koshti, Ajay M.↗

DOE OSTI2022

High-resolution ultra-low field magnetic resonance imaging with a high-sensitivity sensing coil

We present high-resolution magnetic resonance imaging (MRI) at ultra-low field (ULF) with a proton Larmor frequency of around 120 kHz. The key element is a specially designed high-sensitivity sensing coil in the shape of a solenoid with a few millimeter gap between windings to decrease the proximity effect and, hence, increase the coil’s quality ([Formula: see text]) factor and sensitivity. External noise is strongly suppressed by enclosing the sensing coil in a copper cylindrical shield, large enough not to negatively affect the coil’s [Formula: see text] factor and sensitivity, measured to be 217 and 0.47 fT/Hz[Formula: see text], respectively. To enhance small polarization of proton spins at ULF, a strong pulsed 0.1 T prepolarization field is applied, making the signal-to-noise ratio (SNR) of ULF MRI sufficient for high-quality imaging in a short time. We demonstrate ULF MRI of a copper sulfate solution phantom with a resolution of [Formula: see text] and SNR of 10. The acquisition time is 6.3 min without averaging. The sensing coil size in the current realization can accommodate imaging objects of 9 cm in size, sufficient for hand, and it can be further increased for human head imaging in the future. Since the in-plane resolution of [Formula: see text] is typical in anatomical medical imaging, this ULF MRI method can be an alternative low-cost, rapid, portable method for anatomical medical imaging of the human body or animals. This ULF MRI method can supplement other MRI methods, especially when such methods are restricted due to high cost, portability requirement, imaging artifacts, and other factors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Comprehensive characterization of ball-milled powders simulating a tribofilm system

A model system was used to simulate the properties of tribofilms which form during automotive braking. The model system was prepared by ball milling of a blend of 70 vol.% iron oxides, 15 vol.% molybdenum disulfide and 15 vol.% graphite. The resulting mixture was characterized by X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and various transmission electron microscopic (TEM) methods, including energy dispersive X-ray spectroscopy (EDXS), high resolution investigations (HRTEM) with corresponding simulation of the HRTEM images, diffraction methods such as scanning nano-beam electron diffraction (SNBED) and selected area electron diffraction (SAED). It could be shown that the ball milling caused a reduction of the grain size of the initial components to the nanometer range. Sometimes even amorphization or partial break-down of the crystal structure was observed for MoS{sub 2} and graphite. Moreover, chemical reactions lead to a formation of surface coverings of the nanoparticles by amorphous material, molybdenum oxides, and iron sulfates as derived from XPS. - Highlights: • Ball milling of iron oxides, MoS{sub 2}, and graphite to simulate a tribofilm • Increasing coefficient of friction after ball milling of the model blend • Drastically change of the diffraction pattern of the powder mixture • TEM & XPS showed the components of the milled mixture and the process during milling. • MoS{sub 2} and graphite suffered a loss in translation symmetry or became amorphous.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Automated detection of rear contact voids in perc cells with photoluminescence imaging

An image-processing method combined with Fourier analysis is introduced here in this work as a rapid and highly-automated method of detecting rear contact voids in passivated emitter and rear contact cells (PERC). This approach utilizes photoluminescence (PL) imaging to locate the central point of the most detrimental type of voids and associate a void fraction to each cell in a manner of seconds. Acoustic microscopy and scanning electron microscopy are also used as complementary tools to confirm the presence of voids detection using PL imaging and provide more insight into the actual physical mechanism of what is observed in PL measurements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

MO-F-CAMPUS-I-03: Tissue Equivalent Material Phantom to Test and Optimize Coherent Scatter Imaging for Tumor Classification

Purpose: To accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Methods: A breast phantom has been designed to assess the capability of coded aperture coherent x-ray scatter imaging system to classify different types of breast tissue (adipose, fibroglandular, tumor). The tissue-equivalent phantom was modeled as a hollow plastic cylinder containing multiple cylindrical and spherical inserts that can be positioned, rearranged, or removed to model different breast geometries. Each enclosure can be filled with a tissue-equivalent material and excised human tumors. In this study, beef and lard, placed inside 2-mm diameter plastic Nalgene containers, were used as surrogates for fibroglandular and adipose tissue, respectively. The phantom was imaged at 125 kVp, 40 mA for 10 seconds each with a 1-mm pencil beam. The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor, or momentum transfer (q) spectrum of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: The tissue equivalent phantom was found to accurately model different types of breast tissue by qualitatively comparing our measured form factors to those of adipose and fibroglandular tissue from literature. Our imaging system has been able to define the location and composition of the various materials in the phantom. Conclusion: This work introduces a new tissue equivalent phantom for testing and optimization of our coherent scatter imaging system for material classification. In future studies, the phantom will enable the use of a variety of materials including excised human tissue specimens in evaluating and optimizing our imaging system using pencil- and fan-beam geometries. United States Department of Homeland Security Duke University Medical Center - Department of Radiology Carl E Ravin Advanced Imaging Laboratories Duke University Medical Physics Graduate Program.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1976

Interactive imaging and data processing

Image processing method is capable of contrast enhancement, noise filtering, and photometric distortion removal in near real time. System uses digital image integration and digital video recorder as image buffer. Each frame of data is entered into memory; registers provide readout of stored TV frame.

Alsberg, H.↗

DOE OSTI2016

Study on efficiency of time computation in x-ray imaging simulation base on Monte Carlo algorithm using graphics processing unit

Monte Carlo (MC) is one of the powerful techniques for simulation in x-ray imaging. MC method can simulate the radiation transport within matter with high accuracy and provides a natural way to simulate radiation transport in complex systems. One of the codes based on MC algorithm that are widely used for radiographic images simulation is MC-GPU, a codes developed by Andrea Basal. This study was aimed to investigate the time computation of x-ray imaging simulation in GPU (Graphics Processing Unit) compared to a standard CPU (Central Processing Unit). Furthermore, the effect of physical parameters to the quality of radiographic images and the comparison of image quality resulted from simulation in the GPU and CPU are evaluated in this paper. The simulations were run in CPU which was simulated in serial condition, and in two GPU with 384 cores and 2304 cores. In simulation using GPU, each cores calculates one photon, so, a large number of photon were calculated simultaneously. Results show that the time simulations on GPU were significantly accelerated compared to CPU. The simulations on the 2304 core of GPU were performed about 64 -114 times faster than on CPU, while the simulation on the 384 core of GPU were performed about 20 – 31 times faster than in a single core of CPU. Another result shows that optimum quality of images from the simulation was gained at the history start from 10{sup 8} and the energy from 60 Kev to 90 Kev. Analyzed by statistical approach, the quality of GPU and CPU images are relatively the same.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1971

A method of differential field photometry by video-photographic image subtraction

Doppler velocity field recording method over two dimensional solar active region image, using narrow band filter with video photographic subtraction technique

Fisher, R. R.↗

DOE OSTI2023

Systems, methods, and media for high dynamic range imaging using single-photon and conventional image sensor data

In accordance with some embodiments, systems, methods, and media for high dynamic range imaging using single-photon and conventional image sensor data are provided. In some embodiments, the system comprises: first detectors configured to detect a level of photons proportional to incident photon flux; second detectors configured to detect arrival of individual photons; a processor programmed to: receive, from the first detectors, first values indicative of photon flux from a scene with a first resolution; receive, from the second detectors, second values indicative of photon flux from the scene with a lower resolution; provide a first encoder of a trained machine learning model first flux values based on the first values, provide the second encoder of the model second flux values; receive, as output, values indicative of photon flux from the scene; and generate a high dynamic range image based on the third plurality of values.

Gutierrez Barragan, Felipe↗

NASA NTRS2000

A simulator for evaluating methods for the detection of lesion-deficit associations

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

NASA Program Biomedical Research and Countermeasur↗