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DOE OSTI2026

202508 HAIIC IR Images with Attitude Data at BNF

This campaign aims to collect infrared imagery using a custom data acquisition system to improve and validate a previously developed attitude estimation algorithm, with a focus on ensuring reliable performance at higher altitudes. The system integrates a Boson+320 infrared camera, a VN-200 IMU for recording attitude data synchronized with image acquisition, and a Raspberry Pi 4B+ for onboard processing and storage. Image orientation was controlled using a Gremsy T7 gimbal. The primary dataset spans roll angles from −40° to 40° and pitch angles from −20° to 40°, sampled at 1° increments. Additional, smaller datasets were also collected at 2.5° angular intervals.

Boson+320↗

DOE OSTI2021

Infrared intrusion detection system (IRIDS)

A system and method for intrusion detection includes an imager directed towards an object in an interior space. The imager is in data communication with a computer. The computer is arranged to process digital three-dimensional image data received from the imager and programmed to execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object. The computer generates an alarm output in response to detecting movement of the object above a predetermined threshold. The method includes providing an imager directed towards an object in an interior space; receiving Time of Flight signals by the imager; processing digital three-dimensional image data received from the imager; and executing a change detection algorithm in response to the processed three-dimensional data to determine movement of the object.

Russell, John L.↗

DOE OSTI2021

Identification and correction of temporal and spatial distortions in scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be used to map strain, polarization, octahedra tilts, and other physical and chemical order parameter fields. The latter can be used as inputs into mesoscopic and atomistic models, providing insight into the correlative relationships and generative physics of materials on the atomic level. However, these quantitative applications of STEM necessitate understanding the microscope induced image distortions and developing the pathways to compensate them both as part of a rapid calibration procedure for in situ imaging, and the post-experimental data analysis stage. Here, we explore the spatiotemporal structure of the microscopic distortions in STEM using multivariate analysis of the atomic trajectories in the image stacks. Based on the behavior of principal component analysis (PCA), we develop the Gaussian process (GP)-based regression method for quantification of the distortion function. The limitations of such an approach and possible strategies for implementation as a part of in-line data acquisition in STEM are discussed. Here, the analysis workflow is summarized in a Jupyter notebook that can be used to retrace the analysis and analyze the reader's data.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A new data processing technique for Rayleigh-Taylor instability growth experiments

Typical face-on experiments for Rayleigh-Taylor instability study involve the time-resolved radiography of an accelerated foil with line-of-sight of the radiography along the direction of motion. The usual method which derives perturbation amplitudes from the face-on images reverses the actual image transmission procedure, so the obtained results will have a large error in the case of large optical depth. In order to improve the accuracy of data processing, a new data processing technique has been developed to process the face-on images. This technique based on convolution theorem, refined solutions of optical depth can be achieved by solving equations. Furthermore, we discuss both techniques for image processing, including the influence of modulation transfer function of imaging system and the backlighter spatial profile. Besides, we use the two methods to the process the experimental results in Shenguang-II laser facility and the comparison shows that the new method effectively improve the accuracy of data processing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

36 MATERIALS SCIENCE↗

DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗

DOE OSTI2015

A Framework of Hyperspectral Image Compression using Neural Networks

Hyperspectral image analysis has gained considerable attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows us to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. This paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

SU-D-207-01: Markerless Respiratory Motion Tracking with Contrast Enhanced Thoracic Cone Beam CT Projections

Purpose: To develop a novel technique to enhance the image contrast of clinical cone beam CT projections and extract respiratory signals based on anatomical motion using the modified Amsterdam Shroud (AS) method to benefit image guided radiation therapy. Methods: Thoracic cone beam CT projections acquired prior to treatment were preprocessed to increase their contrast for better respiratory signal extraction. Air intensity on raw images was firstly estimated and then applied to correct the projections to generate new attenuation images that were subsequently improved with deeper anatomy feature enhancement through taking logarithm operation, derivative along superior-inferior direction, respectively. All pixels on individual post-processed two dimensional images were horizontally summed to one column and all projections were combined side by side to create an AS image from which patient’s respiratory signal was extracted. The impact of gantry rotation on the breathing signal rendering was also investigated. Ten projection image sets from five lung cancer patients acquired with the Varian Onboard Imager on 21iX Clinac (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Results: Application of the air correction on raw projections showed that more than an order of magnitude of contrast enhancement was achievable. The typical contrast on the raw projections is around 0.02 while that on attenuation images could greater than 0.5. Clear and stable breathing signal can be reliably extracted from the new images while the uncorrected projection sets failed to yield clear signals most of the time. Conclusion: Anatomy feature plays a key role in yielding breathing signal from the projection images using the AS technique. The air correction process facilitated the contrast enhancement significantly and attenuation images thus obtained provides a practical solution to obtaining markerless breathing motion tracking.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Real-Time Data Acquisition and Processing System for MHz Repetition Rate Image Sensors

An electro-optic detector is one of the diagnostic setups used in particle accelerators. It employs an electro-optic crystal to encode the longitudinal beam charge profile in the spectrum of a light pulse. The charge distribution is then reconstructed using data captured by a fast spectrometer. The measurement repetition rate should match or exceed the machine bunching frequency, which is often in the range of several MHz. A high-speed optical line detector (HOLD) is a linear camera designed for easy integration with scientific experiments. The use of modern FPGA circuits helps in the efficient collection and processing of data. The solution is based on Xilinx 7-Series FPGA circuits and implements a custom latency-optimized architecture utilizing the AXI4 family of interfaces. HOLD is one of the fastest line cameras in the world. Thanks to its hardware architecture and a powerful KALYPSO sensor from KIT, it outperforms the fastest comparable commercial devices.

MicroTCA↗

DOE OSTI2018

Hyperspectral Raman imaging using a spatial heterodyne spectrometer (SHS)

Savannah River National Laboratory, and the larger community, has limited chemical-specific imaging capabilities, which would be beneficial for remote detection of threat chemicals or use in inaccessible and harsh environments, as well as in-line process monitoring. Chemical imaging technology would support multiple directorates through stand-off detection of chemicals (National Security), and imaging of chemical distributions in a process (Nuclear Materials Management, Clean Energy) and in waste tanks (Environmental Stewardship). Chemical-specific imaging is underdeveloped due to issues of sensitivity, stable alignment and calibration, and ease of operation associated with most optical instruments. The project objective is to develop a novel, rugged, highly sensitive spectrometer to support real-time, chemically specific imaging using hyperspectral Raman spectroscopy. Raman spectroscopic analysis will provide chemical specificity and using a spatial heterodyne spectrometer (SHS) will increase the sensitivity due to the high light throughput design. The SHS design does not require moving parts allowing for a very stable system, reducing alignment and calibration issues. The instrument will be assembled and initially applied to Raman gas detection of the Saltstone disposal unit headspace gas concentrations. Raman gas analysis is the most impacted by sensitivity issues and will be used to demonstrate the increased light collection capability of the SHS over a conventional dispersive spectrometer. The system will be later modified to image spectral information in a spatial domain to provide information on the spatial distribution of a sample scene.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Revealing particle-scale powder spreading dynamics in powder-bed-based additive manufacturing process by high-speed x-ray imaging

Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. Here, the particle scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.

42 ENGINEERING↗

DOE OSTI2018

Readout models for BaFBr 0.85 I 0.15 :Eu image plates

The linearity of the photostimulated luminescence process makes repeated image-plate scanning a viable technique to extract more dynamic range. In order to obtain a response estimate, two semi-empirical models for the readout fading of an image plate are introduced; they relate the depth distribution of activated photostimulated luminescence centers within an image plate to the recorded signal. Model parameters are estimated from image-plate scan series with BAS-MS image plates and the Typhoon FLA 7000 scanner for the hard x-ray image-plate diagnostic over a collection of experiments providing x-ray energy spectra whose approximate shape is a double exponential.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Measurement of Photovoltaic Module Deformation Dynamics During Hail Impact Using Digital Image Correlation

Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Furthermore, impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.

14 SOLAR ENERGY↗

DOE OSTI2019

Assessing XMT-Measurement Variability of Air-Water Interfacial Areas in Natural Porous Media

This study investigates the accuracy and reproducibility of air-water interfacial areas measured with high-resolution synchrotron X-ray microtomography (XMT). Columns packed with one of two relatively coarse-grained monodisperse granular media, glass beads or a well-sorted quartz sand, were imaged over several years, encompassing changes in acquisition equipment, improved image quality, and enhancements to image acquisition and to processing software. For the glass beads, the specific solid surface area (SSSA-XMT) of 31.6 ± 1 cm -1 determined from direct analysis of the segmented solid-phase image data is statistically identical to the independently calculated geometric smooth-sphere specific solid surface area (GSSA, 32 ± 1 cm -1 ) and to the measured SSSA (28 ± 3 cm -1 ) obtained with the N2-Brunauer, Emmett, and Teller method. The maximum specific air-water interfacial area (Amax) is 27.4 (±2) cm -1 , which compares very well to the SSSA-XMT, GSSA, and SSSA-N2-Brunauer, Emmett, and Teller values. For the sand, the SSSA-XMT (111 ± 2 cm -1 ) and GSSA (113 ± 1 cm -1 ) are similar. The mean Amax is 96 ± 5 cm -1 , which compares well to both the SSSA and the GSSA values. The XMT-SSSA values deviated from the GSSA values by 7–16% for the first four experiments but were essentially identical for the later experiments. This indicates that enhancements in image acquisition and processing improved data accuracy. The Amax values ranged from 74 cm -1 to 101 cm -1 , with a coefficient of variation (COV) of 9%. The maximum capillary interfacial area ranged from 12 cm-1 to 19 cm -1 , for a COV of 10%. The COVs for both decreased to 5–6% for the latter five experiments. These results demonstrate that XMT imaging provides accurate and reproducible measurements of total and capillary interfacial areas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Integrative Quantitative-Phase and Airy Light-Sheet Imaging

Light-sheet microscopy enables considerable speed and phototoxicity gains, while quantitative-phase imaging confers label-free organelle recognition and metabolic information that are inaccessible by conventional methods. We report the fusion of these two modalities onto a standard inverted microscope that retains compatibility with microfluidics. We describe the utilization of an accelerating Airy-beam light-sheet yielding identical imaging areas with interferometry, and an application in unmasking the effects of cellular noise on metabolic compartmentalization.

Biological sciences, Biological techniques, Micros↗

DOE OSTI2024

HyperKube: A Kubernetes Based System for the Automation of Processing and Analysis of Hyperspectral Data Obtained from Multiple Hyperspectral Imaging Systems

Hyperspectral imagery is an emerging field of technology that has enormous potential for remote and proximal sensing in numerous areas of research. The plant phenotyping community is applying this technology to advance the throughput and accuracy of plant phenotypes based on airborne and lab-based hyperspectral imaging technology. Here we report an automated processing and analysis pipeline for four different hyperspectral imaging platforms, discuss the data issues involved, and present a strategy for computing and data architecture to handle hyperspectral data.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Measurement of hybrid rocket solid fuel regression rate for a slab burner using deep learning

This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary layer combustion in hybrid rockets by the measurement of fuel regression rates. A DSLR camera with a high intensity flash is used to capture images throughout the burn and the images are then used to find the fuel boundary to calculate the regression rate. A U-net convolutional neural network architecture is explored to segment the fuel from the experimental images. Here, a Monte-Carlo Dropout process is used to quantify the regression rate uncertainty produced from the network. The U-net computed regression rates are compared with values from other techniques from literature and show error less than 10%. An oxidizer flux dependency study is performed and shows the U-net predictions of regression rates are accurate and independent of the oxidizer flux, when the images in the training set are not over-saturated. Training with monochrome images is explored and is not successful at predicting the fuel regression rate from images with high noise. The network is superior at filtering out noise introduced by soot, pitting, and wax deposition on the chamber glass as well as the flame when compared to traditional image processing techniques, such as threshold binary conversion and spatial filtering. U-net consistently provides low error image segmentations to allow accurate computation of the regression rate of the fuel.

42 ENGINEERING↗

DOE OSTI2015

SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT

Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantify image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)

60 APPLIED LIFE SCIENCES↗