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At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Annotation of images based on a 3D model of objects

An annotation system for providing annotations for original images is provided. In some embodiments, the annotation system accesses an annotation associated with an object of a 3D model. The annotation system also accesses and displays an original image. The annotation system renders a model image of the 3D model based on the view from which the original image was collected. When the model image contains the annotated object, the annotation system provides an indication that an annotation is associated with the object of the original image. The annotation system can provide indications of the annotation for other original images that include the annotated object irrespective of the view from which the other original images are collected.

42 ENGINEERING↗

DOE OSTI2022

System and method for x-ray compatible 2D streak camera for a snapshot multiframe imager

The present disclosure is directed to a snapshot multiframe imager having an aperture element having at least one aperture, an adjacently positioned random mask, an imaging element and a computer. The random mask has a plurality of micron scale apertures and receives light passing through the aperture element, which represents the spatial information from the scene being imaged, and generates a plurality of image frames encoded in a spatial domain. The imaging element may operate in a drift-scan mode receives the encoded image frames and generates a streaked pattern of electrons representing a plurality of images of the scene at a plurality of different times. The computer analyzes the streaked pattern of electrons and mathematically reconstructs the plurality of images.

Dayton, Matthew S.↗

DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗

DOE OSTI2025

Broadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors

We present a broadband and polarization-insensitive unidirectional imager that operates at the visible part of the spectrum, where image formation occurs in one direction, while in the opposite direction, it is blocked. This approach is enabled by deep learning-driven diffractive optical design with wafer-scale nano-fabrication using high-purity fused silica to ensure optical transparency and thermal stability. Our design achieves unidirectional imaging across three visible wavelengths (covering red, green, and blue parts of the spectrum), and we experimentally validated this broadband unidirectional imager by creating high-fidelity images in the forward direction and generating weak, distorted output patterns in the backward direction, in alignment with our numerical simulations. This work demonstrates wafer-scale production of diffractive optical processors, featuring 16 levels of nanoscale phase features distributed across two axially aligned diffractive layers for visible unidirectional imaging. This approach facilitates mass-scale production of ~0.5 billion nanoscale phase features per wafer, supporting high-throughput manufacturing of hundreds to thousands of multi-layer diffractive processors suitable for large apertures and parallel processing of multiple tasks. Beyond broadband unidirectional imaging in the visible spectrum, this study establishes a pathway for artificial-intelligence-enabled diffractive optics with versatile applications, signaling a new era in optical device functionality with industrial-level, massively scalable fabrication.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Understanding ICF hohlraums using NIF gated laser-entrance-hole images

The newly available ns-gated laser-entrance-hole (LEH) imager on the National Ignition Facility provides routine, non-perturbative measurements of the x-ray emission from laser-heated plasmas inside the hohlraum as viewed at 19° to the hohlraum axis through one of its LEHs. Multiple images are acquired for a series of times and filter-selected x-ray energy bands within a single shot. The images provide time dependent data on phenomena including the effective radius of the LEH, the length of the gold-plasma “bubble” evolving off the interior wall surface heated by the outer beams, the evolving radius of the x-ray heated hohlraum wall, and the radius of the ablation front of the fusion capsule. Here, these measurements are explained and illustrated with sample data. These techniques are then applied to understand hohlraum behavior as a function of gas fill. For hohlraums with helium gas fill densities of 0.15 to 0.30 mg/cm 3 , synthetic images computed from simulations agree well with experimental gated LEH images when an inhibited heat transport model [Jones et al., Phys. Plasmas 24, 056312 (2017)] is used. This model can be adjusted to reproduce the expansion rate of the laser-heated plasma bubble in such a way as to improve agreement with the images. At the higher 0.6 mg/cc gas fill, the experimental images show more pronounced 3D features, resulting in slightly less good agreement with the 2D simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Dynamic Differential Image Circle Diameter Measurement Precision Assessment: Application to Burning Droplets

Dynamic measurement precision assessment has been achieved for a differential circle measurement application. Differential circle diameter measurement, in image analysis, typically requires fitting a circle model that optimizes for image distortions, defects or occlusions. The differential task occurs when precise measurements of diameter change are required given object size variation with time. An automated system was designed to provide diameter measurements and associated measurement precision of images of a fuel droplet undergoing combustion in zero gravity for the FLEX-2 dataset. An image gradient-based, least-squares boundary point fitting method to a circle or ellipse model is used for diameter measurement. The presence of soot aggregates poses significant challenges for diameter measurements when it occludes part of the droplet boundary. The precision of the diameter measurements depends upon the image quality. Using synthetic image simulations that model the soot behavior, we developed a model based on image quality measures that assesses the measurement precision for each individual diameter measurement. Thus, diameter measurements with precision assessments were made available for follow-up scientific analysis. As a result, the algorithm's success rate for measurable runs was 98%. In cases of limited occlusion, a measurement precision of ±0.2 pixels for the FLEX-2 dataset was achieved.

42 ENGINEERING↗

DOE OSTI2023

Performance Comparison of Object Detection Networks for Shrapnel Identification in Ultrasound Images

Ultrasound imaging is a critical tool for triaging and diagnosing subjects but only if images can be properly interpreted. Unfortunately, in remote or military medicine situations, the expertise to interpret images can be lacking. Machine-learning image interpretation models that are explainable to the end user and deployable in real time with ultrasound equipment have the potential to solve this problem. We have previously shown how a YOLOv3 (You Only Look Once) object detection algorithm can be used for tracking shrapnel, artery, vein, and nerve fiber bundle features in a tissue phantom. However, real-time implementation of an object detection model requires optimizing model inference time. Here, we compare the performance of five different object detection deep-learning models with varying architectures and trainable parameters to determine which model is most suitable for this shrapnel-tracking ultrasound image application. We used a dataset of more than 16,000 ultrasound images from gelatin tissue phantoms containing artery, vein, nerve fiber, and shrapnel features for training and evaluating each model. Every object detection model surpassed 0.85 mean average precision except for the detection transformer model. Overall, the YOLOv7tiny model had the higher mean average precision and quickest inference time, making it the obvious model choice for this ultrasound imaging application. Other object detection models were overfitting the data as was determined by lower testing performance compared with higher training performance. In summary, the YOLOv7tiny object detection model had the best mean average precision and inference time and was selected as optimal for this application. Next steps will implement this object detection algorithm for real-time applications, an important next step in translating AI models for emergency and military medicine.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

High-Density Polyethylene Custom Focusing Lenses for High-Resolution Transient Terahertz Biomedical Imaging Sensors

Transient terahertz time-domain spectroscopy (THz-TDS) imaging has emerged as a novel non-ionizing and noninvasive biomedical imaging modality, designed for the detection and characterization of a variety of tissue malignancies due to their high signal-to-noise ratio and submillimeter resolution. We report our design of a pair of aspheric focusing lenses using a commercially available lens-design software that resulted in about 200 × 200-μm2 focal spot size corresponding to the 1-THz frequency. The lenses are made of high-density polyethylene (HDPE) obtained using a lathe fabrication and are integrated into a THz-TDS system that includes low-temperature GaAs photoconductive antennae as both a THz emitter and detector. The system is used to generate high-resolution, two-dimensional (2D) images of formalin-fixed, paraffin-embedded murine pancreas tissue blocks. The performance of these focusing lenses is compared to the older system based on a pair of short-focal-length, hemispherical polytetrafluoroethylene (TeflonTM) lenses and is characterized using THz-domain measurements, resulting in 2D maps of the tissue refractive index and absorption coefficient as imaging markers. For a quantitative evaluation of the lens effect on the image resolution, we formulated a lateral resolution parameter, R2080, defined as the distance required for a 20–80% transition of the imaging marker from the bare paraffin region to the tissue region in the same image frame. The R2080 parameter clearly demonstrates the advantage of the HDPE lenses over TeflonTM lenses. The lens-design approach presented here can be successfully implemented in other THz-TDS setups with known THz emitter and detector specifications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Exploiting voxel-sparsity for bone imaging with sparse-view cone-beam computed tomography

An optimization-based image reconstruction frame work is developed specifically for bone imaging. This framework exploits voxel-sparsity by use of ℓ 1 -norm image regularization and it enables image reconstruction from sparse-view cone-beam computed tomography (CBCT) acquisition. The effectiveness of the voxel-sparsity regularization is enhanced by using a blurred image representation. Ramp-filtering is included in the data discrepancy term and it has the effect of acting as a preconditioner, reducing the necessary number of iterations. The bone image reconstruction framework is demonstrated on CBCT data taken from an equine metacarpal condyle specimen.

Bone imaging↗

DOE OSTI2021

Hyperdimensional Imaging Contrast Using an Optical Fiber

Fluorescence properties of a molecule can be used to study the structural and functional nature of biological processes. Physical properties, including fluorescence lifetime, emission spectrum, emission polarization, and others, help researchers probe a molecule, produce desired effects, and infer causes and consequences. Correlative imaging techniques such as hyperdimensional imaging microscopy (HDIM) combine the physical properties and biochemical states of a fluorophore. Here we present a fiber-based imaging system that can generate hyper-dimensional contrast by combining multiple fluorescence properties into a single fluorescence lifetime decay curve. Fluorescence lifetime imaging microscopy (FLIM) with controlled excitation polarization and temporally dispersed emission can generate a spectrally coded, polarization-filtered lifetime distribution for a pixel. This HDIM scheme generates a better contrast between different molecules than that from individual techniques. This setup uses only a single detector and is simpler to implement, modular, cost-efficient, and adaptable to any existing FLIM microscope. We present higher contrast data from Arabidopsis thaliana epidermal cells based on intrinsic anthocyanin emission properties under multiphoton excitation. This work lays the foundation for an alternative hyperdimensional imaging system and demonstrates that contrast-based imaging is useful to study cellular heterogeneity in biological samples.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Analysis of an optical imaging system prototype for autonomously monitoring zooplankton in an aquaculture facility

Traditional approaches to biomonitoring in aquatic systems, such as sample collection, sorting, and identification, require significant time and effort, thereby limiting the spatiotemporal resolution of sample collection. Additionally, collection and preservation of samples for subsequent taxonomic identification and enumeration leads to mortality of organisms. Recent advances in technologies that utilize optical imaging and machine learning have provided new opportunities to expedite biomonitoring and lead to significant cost savings. These technologies can be advantageous to scientists or managers that conduct routine biomonitoring to inform operations, as in the case of aquaculture facilities. The Small Aquatic Organism optical imaging system (SAO) is a high-throughput optical imaging and classification prototype system that relies on computer vision and machine learning (Support Vector Machines, or SVMs) to autonomously identify and enumerate aquatic organisms. The SAO provides a more sustainable method of collecting large volumes of data and has the benefit of being used in situ. In this study, we tested the performance of the SAO in providing comparable results to manual zooplankton community monitoring in ten ponds at an aquaculture facility. We performed a side-by-side study comparing the sampling methods of plankton tow nets, where major zooplankton taxonomic classes were manually identified and enumerated, to sampling with the SAO. Vouchered samples were used to develop a training library for the SAO, where classes consisted of water boatman and zooplankton groups: cladocerans, copepod adults, copepod nauplii, and rotifers. SAO imagery was manually classified and compared with predicted results for validation. Accuracy for the SVM classifier of the SAO was 37.4 %. Convolutional Neural Networks (CNN) and Random Forest classifiers were also applied to SAO imagery and image features for comparison. The best CNN model and our Random Forest model had accuracies of 80.4 % and 46.6 % respectively. Challenges faced included the small size of copepod nauplii and rotifers and the limited resolution of the imaging camera, although there are tradeoffs between imaging resolution and the sample processing rate. Furthermore, our comparison shows that advancement in both optical imaging and ML are needed in order for the SAO prototype to yield comparable results to manual community monitoring in an aquaculture facility.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Quantitative investigation of sooting dynamics in droplet combustion using an automated image analysis algorithm

This paper reports an image analysis approach using a newly-developed open-source program to extract quantitative measurements of soot volume fraction (SVF) from digital video images of burning n-heptane droplets. The automated program developed in this work can analyze images of fixed and untethered droplets to quantify sooting dynamics. The images analyzed in the program were taken from experiments carried out in the Multi-user Droplet Combustion Apparatus (MDCA) onboard the International Space Station (ISS). In these experiments, video imaging of burning droplets was obtained using backlighting by a laser diode with a wavelength of 653 nm. Here, the light was collimated before it passed through the droplet and soot-containing region, after which the light was then attenuated and projected onto the camera’s sensors. This technique facilitates the measurements of SVF based on the principles of the full field light extinction method (FFLEM). The measurements provide quantitative data that reveal the sooting dynamics of liquid fuels during droplet combustion processes. The analyses of a soot-attenuating image (ISS n-heptane, untethered droplet) at an instant during the burning show that the SVF distribution has a peak at the soot shell location. It then decreases due to soot oxidation when the location is further away from the burning droplet. Regarding temporal effects on the maximum SVF (SVF max ), results show that SVF max first increases after the burning is initiated until a peak value is reached, after which SVF max decreases. The SVF max values identified in this study for n-heptane are quantitatively consistent with previously reported values for fiber-supported droplets and are reached relatively early in the burning history. n-Heptane images are also analyzed to show the effects of initial droplet sizes on the maximum soot volume fraction. Results show that SVF max decreases with increasing initial droplet size, which is consistent with visual observations of less soot formed and dimmer flame brightness as Do increases.

42 ENGINEERING↗

DOE OSTI2021

High-Resolution Imaging of Unstained Polymer Materials

Electron microscopy has played an important role in polymer characterization. Traditionally, electron diffraction is used to study crystalline polymers while transmission electron microscopy is used to study microphase separation in stained block copolymers and other multiphase systems. We describe developments that eliminate the barrier between these two approaches - it is now possible to image polymer crystals with atomic resolution. The focus of this Review is on high-resolution imaging (30 Å and smaller) of unstained polymers. Recent advances in hardware allow for capturing numerous (as many as 105) low-dose images from an unperturbed specimen; beam damage is a significant barrier to high-resolution electron microscopy of polymers. Machine-learning-based software is then used to sort and average the images to retrieve pristine structural information from a collection of noisy images. Acknowledging the heterogeneity in polymer samples prior to averaging is essential. Molecular conformations in a wide range of amphiphilic block copolymers, polymerized ionic liquids, and conjugated polymers can be gleaned from two-dimensional projections (2D), three-dimensional (3D) tomograms, and four-dimensional (4D) scanning transmission electron microscopy (STEM) data sets where 2D diffraction patterns are taken as a function of position. Some methods such as phase contrast STEM have been used to image closely related materials such as metal-organic frameworks but not polymers. With improvements in hardware and software, such methods may soon be applied to polymers. Our goal is to provide a comprehensive understanding of the strategies toward the high-resolution imaging of radiation sensitive polymer materials at different length scales.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Integrated photonic encoder for low power and high-speed image processing

Abstract Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Image processing tools for petabyte-scale light sheet microscopy data

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Correlative single-cell hard X-ray computed tomography and X-ray fluorescence imaging

Abstract X-ray computed tomography (XCT) and X-ray fluorescence (XRF) imaging are two non-invasive imaging techniques to study cellular structures and chemical element distributions, respectively. However, correlative X-ray computed tomography and fluorescence imaging for the same cell have yet to be routinely realized due to challenges in sample preparation and X-ray radiation damage. Here we report an integrated experimental and computational workflow for achieving correlative multi-modality X-ray imaging of a single cell. The method consists of the preparation of radiation-resistant single-cell samples using live-cell imaging-assisted chemical fixation and freeze-drying procedures, targeting and labeling cells for correlative XCT and XRF measurement, and computational reconstruction of the correlative and multi-modality images. With XCT, cellular structures including the overall structure and intracellular organelles are visualized, while XRF imaging reveals the distribution of multiple chemical elements within the same cell. Our correlative method demonstrates the feasibility and broad applicability of using X-rays to understand cellular structures and the roles of chemical elements and related proteins in signaling and other biological processes.

59 BASIC BIOLOGICAL SCIENCES↗