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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Real-time High-resolution X-Ray Computed Tomography

Computed Tomography (CT) serves as a key imaging technology that relies on computationally intensive filtering and back-projection algorithms for 3D image reconstruction. While conventional high-resolution image reconstruction (> 2K3) solutions provide quick results, they typically treat reconstruction as an offline workload to be performed remotely on large-scale HPC systems. The growing demand for post-construction AI-driven analytics and the need for real-time adjustments call for high-resolution reconstruction solutions that are feasible on local computing resources, i.e. a multi-GPU server at most. In this paper, we propose a novel approach that utilizes Tensor Cores to optimize image reconstruction without sacrificing precision. We also introduce a framework designed to enable real-time execution of end-to-end distributed image reconstruction in a multi-GPU environment. Evaluations conducted on a single Nvidia A100 and H100 GPU show performance improvements of 1.91 × and 2.15 × compared to highly optimized production libraries. Furthermore, our framework, when deployed on 8-card Nvidia A100 GPU system, demonstrates the ability to reconstruct real-world datasets into 20483 volumes (32 GB) in slightly more than one minute and 40963 volumes (256 GB) in 7 minutes.

Wu, Du↗

A New Workflow of X-ray CT Image Processing and Data Analysis of Structural Features in Rock Using Open-Source Software

X-ray computed tomography (CT) images of rock specimens often contain artifacts which must be corrected before scientific analyses are performed. Here, we present a new workflow of automated image processing to utilize poor-quality X-ray CT scan images. The workflow runs on the open-source image analysis software and efficiently separates desired features from low-contrast scanned images. The new workflow is a two-step technique using contrast enhancement and automated feature segmentation to generate noise-free binary images. The results of binary images using the proposed workflow and using a conventional thresholding technique are analyzed to show the quality of the proposed method. The paper also presents a workflow of estimating the structural geometries of features in two and three dimensions. The results of the structural feature analyses and computational time were compared between the open-source (ImageJ) and commercial image analysis software (Bruker Computed Tomography Analyzer). The commercial software was more computationally efficient, but the task-specific macros in open-source software enabled the user-desired automation in image processing and data extraction of desired structural features of comparable quality.

47 OTHER INSTRUMENTATION↗

First-In-Human Validation of CT-Based Proton Range Prediction Using Prompt Gamma Imaging in Prostate Cancer Treatments

Uncertainty in computed tomography (CT)-based range prediction substantially impairs the accuracy of proton therapy. Direct determination of the stopping-power ratio (SPR) from dual-energy CT (DECT) has been proposed (DirectSPR), and initial validation studies in phantoms and biological tissues have proven a high accuracy. However, a thorough validation of range prediction in patients has not yet been achieved by any means. Here, we present the first systematic validation of CT-based proton range prediction in patients using prompt gamma imaging (PGI).

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Risk of hematological malignancies from CT radiation exposure in children, adolescents and young adults

Over one million European children undergo computed tomography (CT) scans annually. Although moderate- to high-dose ionizing radiation exposure is an established risk factor for hematological malignancies, risks at CT examination dose levels remain uncertain. Here we followed up a multinational cohort (EPI-CT) of 948,174 individuals who underwent CT examinations before age 22 years in nine European countries. Radiation doses to the active bone marrow were estimated on the basis of body part scanned, patient characteristics, time period and inferred CT technical parameters. We found an association between cumulative dose and risk of all hematological malignancies, with an excess relative risk of 1.96 (95% confidence interval 1.10 to 3.12) per 100 mGy (790 cases). Similar estimates were obtained for lymphoid and myeloid malignancies. Results suggest that for every 10,000 children examined today (mean dose 8 mGy), 1–2 persons are expected to develop a hematological malignancy attributable to radiation exposure in the subsequent 12 years. Our results strengthen the body of evidence of increased cancer risk at low radiation doses and highlight the need for continued justification of pediatric CT examinations and optimization of doses.

60 APPLIED LIFE SCIENCES↗

Imaging of the hip joint. Computed tomography versus magnetic resonance imaging

The authors reviewed the applications and limitations of computed tomography (CT) and magnetic resonance (MR) imaging in the assessment of the most common hip disorders. Magnetic resonance imaging is the most sensitive technique in detecting osteonecrosis of the femoral head. Magnetic resonance reflects the histologic changes associated with osteonecrosis very well, which may ultimately help to improve staging. Computed tomography can more accurately identify subchondral fractures than MR imaging and thus remains important for staging. In congenital dysplasia of the hip, the position of the nonossified femoral head in children less than six months of age can only be inferred by indirect signs on CT. Magnetic resonance imaging demonstrates the cartilaginous femoral head directly without ionizing radiation. Computed tomography remains the imaging modality of choice for evaluating fractures of the hip joint. In some patients, MR imaging demonstrates the fracture even when it is not apparent on radiography. In neoplasm, CT provides better assessment of calcification, ossification, and periosteal reaction than MR imaging. Magnetic resonance imaging, however, represents the most accurate imaging modality for evaluating intramedullary and soft-tissue extent of the tumor and identifying involvement of neurovascular bundles. Magnetic resonance imaging can also be used to monitor response to chemotherapy. In osteoarthrosis and rheumatoid arthritis of the hip, both CT and MR provide more detailed assessment of the severity of disease than conventional radiography because of their tomographic nature. Magnetic resonance imaging is unique in evaluating cartilage degeneration and loss, and in demonstrating soft-tissue alterations such as inflammatory synovial proliferation.

Review↗

System and method for identifying objects of interest in images based on likelihood map decluttering

An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.

Paglieroni, David W.↗

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

NASA Center ARC↗

Three-dimensional surface reconstruction for industrial computed tomography

Modern high resolution medical computed tomography (CT) scanners can produce geometrically accurate sectional images of many types of industrial objects. Computer software has been developed to convert serial CT scans into a three-dimensional surface form, suitable for display on the scanner itself. This software, originally developed for imaging the skull, has been adapted for application to industrial CT scanning, where serial CT scans thrrough an object of interest may be reconstructed to demonstrate spatial relationships in three dimensions that cannot be easily understood using the original slices. The methods of three-dimensional reconstruction and solid modeling are reviewed, and reconstruction in three dimensions from CT scans through familiar objects is demonstrated.

Vannier, M. W.↗

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗

The Inside View

Bio-Imaging Research, Inc., has been included in Spinoff 1990 and 1993 with spinoffs from their ACTIS (Advanced Computed Tomography Inspection System) product developed under a Marshall Space Flight Center SBIR (Small Business Innovative Research) contract. The latest application is for noninvasive nuclear waste drum inspection. With the ACTIS CT (computed tomography, CATScan) scanner, radioactive waste is examined to prove that they do not contain one-half percent free liquid or that the drum wall has lost integrity before being moved across state lines or before being permanently disposed.

Source record↗

A wide-field micro-computed tomography detector: micron resolution at half-centimetre scale

Ideal three-dimensional imaging of complex samples made up of micron-scale structures extending over mm to cm, such as biological tissues, requires both wide field of view and high resolution. For existing optics and detectors used for micro-CT (computed tomography) imaging, sub-micron pixel resolution can only be achieved for fields of view of <2 mm. This article presents a unique detector system with a 6 mm field-of-view image circle and 0.5 µm pixel size that can be used in micro-CT units utilizing both synchrotron and commercial X-ray sources. A resolution-test pattern with linear microstructures and whole adult Daphnia magna were imaged at beamline 8.3.2 of the Berkeley Advanced Light Source. Volumes of 10000 × 10000 × 7096 isotropic 0.5 µm voxels were reconstructed over a 5.0 mm × 3.5 mm field of view. Measurements in the projection domain confirmed a 0.90 µm measured spatial resolution that is largely Nyquist-limited. This unprecedented combination of field of view and resolution dramatically reduces the need for sectional scans and computational stitching for large samples, ultimately offering the means to elucidate changes in tissue and cellular morphology in the context of larger, whole, intact model organisms and specimens. This system is also anticipated to benefit micro-CT imaging in materials science, microelectronics, agricultural science and biomedical engineering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging

In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical tests are used to investigate the mechanical properties of bone in relation to its microstructure. Low-dose computed tomography (CT) is used to preserve bone's mechanical properties from radiation damage, though it increases noise. To reduce this noise, the self-supervised deep learning method Noise2Inverse was used on low-dose SRµCT images where segmentation using traditional thresholding techniques was not possible. Simulated-dose datasets were created by sampling projection data at full, one-half, one-third, one-fourth and one-sixth frequencies of an in situ SRµCT mechanical test. After convolutional neural networks were trained, Noise2Inverse performance on all dose simulations was assessed visually and by analyzing bone microstructural features. Visually, high image quality was recovered for each simulated dose. Lacunae volume, lacunae aspect ratio and mineralization distributions shifted slightly in full, one-half and one-third dose network results, but were distorted in one-fourth and one-sixth dose network results. Following this, new models were trained using a larger dataset to determine differences between full dose and one-third dose simulations. Significant changes were found for all parameters of bone microstructure, indicating that a separate validation scan may be necessary to apply this technique for microstructure quantification. Noise present during data acquisition from the testing setup was determined to be the primary source of concern for Noise2Inverse viability. While these limitations exist, incorporating dose calculations and optimal imaging parameters enables self-supervised deep learning methods such as Noise2Inverse to be integrated into existing experiments to decrease radiation dose.

Obata, Yoshihiro (ORCID:0000000303659129)↗

Different CT slice thickness and contrast‐enhancement phase in radiomics models on the differential performance of lung adenocarcinoma

Abstract Background To investigate the effects of computed tomography (CT) reconstruction slice thickness and contrast‐enhancement phase on the differential diagnosis performance of radiomic signature in lung adenocarcinoma. Methods A total of 187 patients who had been pathologically confirmed with lung adenocarcinoma and nonadenocarcinoma were divided into a training cohort ( n = 149) and validation cohort ( n = 38). All the patients underwent contrast‐enhanced CT and the images were reconstructed with different slice thickness. The radiomic features were extracted from different slice thickness and scan phase. The logistic regression (LR) algorithm was used to build a machine learning model for each group. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve and DeLong test was used to evaluate its discriminating performance. Results Finally, 34 image features and five semantic features were selected to establish a radiomics model. Based on the three contrast‐enhanced CT phases and four reconstruction slice thickness, 12 groups of radiomics models showed good discrimination ability with the AUCs range from 0.9287 to 0.9631, sensitivity range from 0.8349 to 0.9083, specificity range from 0.825 to 0.925 in the training group. Similar results were observed in the validation group. However, there was no statistical significance between the different CT scan phase groups and different slice thickness ( p > 0.05). Conclusions The radiomic analysis of contrast‐enhanced CT can be used for the differential diagnosis of lung adenocarcinoma. Moreover, different slice thickness and contrast‐enhanced scan phase did not affect the discriminating ability in the radiomics models.

Wang, Yang↗

Low-Cost X-Ray CT System for Imaging of Roots

The goal of this project was to develop and demonstrate an innovative, low cost, field deployable, stationary 3D x-ray computed tomography (CT) system that will image total root phenotypes with a micron size resolution at a throughput of hundreds of plants per cycle. This system is based on UHV’s unique low cost linear x-ray tube technology and sophisticated reconstruction & image segmentation algorithms developed at University of Massachusetts, Lowel and University of Nottingham; and was tested for several types of soils at University of Wisconsin and Texas A&M University. Currently, no technologies exist that have been designed to image roots in complex media such as agricultural field conditions. Due to its small size, high resolution & fast imaging of fine roots, low power consumption, large penetration depth (i.e. ability to see through several feet of soil) and ease of field deployability, this CT system will increase the speed and efficacy of discovery, field translation, and deployment of improved crops and systems that improve soil carbon accumulation and storage, decrease N2O emissions, and improve water efficiency leading towards advancements that could mitigate 10% of the total US Greenhouse gases. This degree of imaging in the field has never been available and would be invaluable to scientists in understanding how environmental conditions and phenotypic variations contribute to carbon deposition through root development.

54 ENVIRONMENTAL SCIENCES↗

Time-Domain Terahertz Computed Axial Tomography NDE System

NASA has identified the need for advanced non-destructive evaluation (NDE) methods to characterize aging and durability in aircraft materials to improve the safety of the nation's airline fleet. 3D THz tomography can play a major role in detection and characterization of flaws and degradation in aircraft materials, including Kevlar-based composites and Kevlar and Zylon fabric covers for soft-shell fan containment where aging and durability issues are critical. A prototype computed tomography (CT) time-domain (TD) THz imaging system has been used to generate 3D images of several test objects including a TUFI tile (a thermal protection system tile used on the Space Shuttle and possibly the Orion or similar capsules). This TUFI tile had simulated impact damage that was located and the depth of damage determined. The CT motion control gan try was designed and constructed, and then integrated with a T-Ray 4000 control unit and motion controller to create a complete CT TD-THz imaging system prototype. A data collection software script was developed that takes multiple z-axis slices in sequence and saves the data for batch processing. The data collection software was integrated with the ability to batch process the slice data with the CT TD-THz image reconstruction software. The time required to take a single CT slice was decreased from six minutes to approximately one minute by replacing the 320 ps, 100-Hz waveform acquisition system with an 80 ps, 1,000-Hz waveform acquisition system. The TD-THZ computed tomography system was built from pre-existing commercial off-the-shelf subsystems. A CT motion control gantry was constructed from COTS components that can handle larger samples. The motion control gantry allows inspection of sample sizes of up to approximately one cubic foot (.0.03 cubic meters). The system reduced to practice a CT-TDTHz system incorporating a COTS 80- ps/l-kHz waveform scanner. The incorporation of this scanner in the system allows acquisition of 3D slice data with better signal-to-noise using a COTS scanner rather than the gchirped h scanner. The system also reduced to practice a prototype for commercial CT systems for insulating materials where safety concerns cannot accommodate x-ray. A software script was written to automate the COTS software to collect and process TD-THz CT data.

Zimdars, David↗

A CAD Approach to Integrating NDE With Finite Element

Nondestructive evaluation (NDE) is one of several technologies applied at NASA Glenn Research Center to determine atypical deformities, cracks, and other anomalies experienced by structural components. NDE consists of applying high-quality imaging techniques (such as x-ray imaging and computed tomography (CT)) to discover hidden manufactured flaws in a structure. Efforts are in progress to integrate NDE with the finite element (FE) computational method to perform detailed structural analysis of a given component. This report presents the core outlines for an in-house technical procedure that incorporates this combined NDE-FE interrelation. An example is presented to demonstrate the applicability of this analytical procedure. FE analysis of a test specimen is performed, and the resulting von Mises stresses and the stress concentrations near the anomalies are observed, which indicates the fidelity of the procedure. Additional information elaborating on the steps needed to perform such an analysis is clearly presented in the form of mini step-by-step guidelines.

Abdul-Aziz, Ali↗

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles

Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging because of the strong attenuation of the x-ray beam by the uranium core, leading to severe photon starvation in a substantial fraction of the measurements. Furthermore, the overall acquisition time for a high-resolution CT scan can be very long when using conventional laboratory-based x-ray systems and reconstruction algorithms. Specifically, when analytic methods such as the Feldkamp–Davis–Kress (FDK) algorithm are used for reconstruction, it results in severe streak artifacts and noise in the corresponding 3D volume, which makes subsequent analysis of the particles challenging. In this paper, we develop and apply model-based image reconstruction (MBIR) algorithms to improve the quality of CT reconstructions for TRISO particles to facilitate better characterization. We demonstrate that the proposed MBIR algorithms can significantly suppress artifacts with minimal pre-processing compared to conventional approaches. We also demonstrate that the proposed MBIR approach can obtain high-quality reconstruction compared to the FDK approach even when using a fraction of the typically acquired measurements, thereby enabling dramatically faster measurement times for TRISO particles.

Venkatakrishnan, Singanallur↗