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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

TU-H-206-03: Characterizing B1 Inhomogeneities in DCE MRI

Purpose: Dynamic Contrast Enhanced (DCE) MRI is a valuable technique for measuring perfusion and permeability characteristics of tumors. Exogenous contrast concentrations are calculated based on changes in T{sub 1} measured using fast 3D gradient echo (FLASH) sequences. However, the slab selective pulses used in 3D MRI may result in B{sub 1} inhomogeneities across the volume of interest that can lead to errors in T{sub 1} and thus the estimated gadolinium concentration. We compared three FLASH DCE sequences (GRE, TWIST, and VIBE) to determine their signal homogeneity across slices and the accuracy in calculating T{sub 1} using acquisitions with variable flip angles. Methods: The sequences were tested at 3 T on a Siemens mMR (VB20P) using a doped water phantom 3.75 g/L NiSO{sub 4} - 6H{sub 2}O + 5 g/L NaCl (T{sub 1} = 104 ms) and a 2% agar, 0.67% NaCl phantom (T{sub 1}= 1.71 s). 2D EPI B{sub 1} maps and inversion recovery T{sub 1}maps were acquired for ground truth. 3D MRI was acquired at different flip angles to generate a T{sub 1} map. Regions of interest were drawn to measure signal inside the phantoms as a function of slice position. The T{sub 1} for each slice ROI was fit to the FLASH steady-state model of magnetization. Results: Based on the data, GRE gave the most uniform signal homogeneity and T{sub 1} values in the middle slices of the 3D volume. The 3D VIBE sequence had the largest region of signal inhomogeneity compared to the 3D GRE and TWIST sequences. VIBE’s B{sub 1} inhomogeneity is inconsistent at low flip angles. However, VIBE resulted in more slices with T{sub 1} values similar to the ground truth. Conclusion: The central 1/3 of the slices yielded signals that result in T{sub 1} fits consistent with the ground truth. However, the remaining slices required some form of B{sub 1} inhomogeneity correction for quantitative DCE analysis. The research was supported in part by NIH NCI Grant R01CA159471.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1975

Scanning thermal plumes

Over a three-year period 800 thermal line scans of power plant plumes were made by an airborne scanner, with ground truth measured concurrently at the plants. Computations using centered finite differences in the thermal scanning imagery show a lower bound in the horizontal temperature gradient in excess of 1.6 C/m. Gradients persist to 3 m below the surface. Vector plots of the velocity of thermal fronts are constructed by tracing the front motion in successive thermal images. A procedure is outlined for the two-point ground calibration of a thermal scanner from an equation describing the scanner signal and the voltage for two known temperatures. The modulation transfer function is then calculated by input of a thermal step function and application of digital time analysis techniques using Fast Fourier Transforms to the voltage output. Field calibration tests are discussed. Data accuracy is limited by the level of ground truth effort chosen.

Scarpace, F. L.↗
DOE OSTI2012

The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology

Purpose: In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological {sup 18}F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders. Methods: Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of {sup 18}F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of {sup 18}F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax-abdomen phantom and imaged with a PET-CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites' PET threshold segmentations in terms of Dice index and volume error. Results: The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R{sup 2}= 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the {sup 18}F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable borders, as demonstrated by a mean absolute volume error of 2.8% with respect to the PET threshold segmentation corresponding to the maximum Dice. Conclusions: The proposed methodology allowed obtaining an experimental phantom data set that can be used as a feasible tool to test and validate quantification and segmentation algorithms for PET in oncology. The phantom is currently under consideration for being included in a benchmark designed by AAPM TG211, which will be available to the community to evaluate PET automatic segmentation methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Dynamic volume vs respiratory correlated 4DCT for motion assessment in radiation therapy simulation

Purpose: Conventional (i.e., respiratory-correlated) 4DCT exploits the repetitive nature of breathing to provide an estimate of motion; however, it has limitations due to binning artifacts and irregular breathing in actual patient breathing patterns. The aim of this work was to evaluate the accuracy and image quality of a dynamic volume, CT approach (4D{sub vol}) using a 320-slice CT scanner to minimize these limitations, wherein entire image volumes are acquired dynamically without couch movement. This will be compared to the conventional respiratory-correlated 4DCT approach (RCCT). Methods: 4D{sub vol} CT was performed and characterized on an in-house, programmable respiratory motion phantom containing multiple geometric and morphological ''tumor'' objects over a range of regular and irregular patient breathing traces obtained from 3D fluoroscopy and compared to RCCT. The accuracy of volumetric capture and breathing displacement were evaluated and compared with the ground truth values and with the results reported using RCCT. A motion model was investigated to validate the number of motion samples needed to obtain accurate motion probability density functions (PDF). The impact of 4D image quality on this accuracy was then investigated. Dose measurements using volumetric and conventional scan techniques were also performed and compared. Results: Both conventional and dynamic volume 4DCT methods were capable of estimating the programmed displacement of sinusoidal motion, but patient breathing is known to not be regular, and obvious differences were seen for realistic, irregular motion. The mean RCCT amplitude error averaged at 4 mm (max. 7.8 mm) whereas the 4D{sub vol} CT error stayed below 0.5 mm. Similarly, the average absolute volume error was lower with 4D{sub vol} CT. Under irregular breathing, the 4D{sub vol} CT method provides a close description of the motion PDF (cross-correlation 0.99) and is able to track each object, whereas the RCCT method results in a significantly different PDF from the ground truth, especially for smaller tumors (cross-correlation ranging between 0.04 and 0.69). For the protocols studied, the dose measurements were higher in the 4D{sub vol} CT method (40%), but it was shown that significant mAs reductions can be achieved by a factor of 4-5 while maintaining image quality and accuracy. Conclusions: 4D{sub vol} CT using a scanner with a large cone-angle is a promising alternative for improving the accuracy with which respiration-induced motion can be characterized, particularly for patients with irregular breathing motion. This approach also generates 4DCT image data with a reduced total scan time compared to a RCCT scan, without the need for image binning or external respiration signals within the 16 cm scan length. Scan dose can be made comparable to RCCT by optimization of the scan parameters. In addition, it provides the possibility of measuring breathing motion for more than one breathing cycle to assess stability and obtain a more accurate motion PDF, which is currently not feasible with the conventional RCCT approach.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1975

Application of remote sensing for fishery resources assessment and monitoring

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Savastano, K. J.↗
NASA NTRS1981

Ground-truth measurement systems

Ground-truth measurements of precipitation and related weather events are an essential component of any satellite system designed for monitoring rainfall from space. Such measurements are required for testing, evaluation, and operations; they provide detailed information on the actual weather events, which can then be compared with satellite observations intended to provide both quantitative and qualitative information about them. Also, very comprehensive ground-truth observations should lead to a better understanding of precipitation fields and their relationships to satellite data. This process serves two very important functions: (a) aiding in the development and interpretation of schemes of analyzing satellite data, and (b) providing a continuing method for verifying satellite measurements.

Serafin, R.↗
NASA NTRS1988

Relations between VAS physical retrievals and their first guess input

The Smith (1983) physical retrieval algorithm, which is designed to yield mesoscale soundings through a blending of first-guess limited fine mesh-derived profiles with VISSR Atmospheric Sounder (VAS) detected radiance data by means of an inversion of the radiative transfer equation, yields retrievals that may be better related to ground truth data than the guess profiles at some levels. At other levels, the first-guess profiles were slightly superior to the retrievals. Correlation functions related to the window and midtropospheric temperature channels indicate that magnitudes and orientations of retrieval gradients were intermediate to those of the guess data and brightness temperatures.

Beven, John L.↗
NASA NTRS1975

Radar backscatter properties of milo and soybeans

The radar backscatter from fields of milo and soybeans was measured with a ground based radar as a function of frequency (8-18 GHz), polarization (HH and VV) and angle of incidence (0 deg-70 deg) during the summer of 1974. Supporting ground truth was gathered contemporaneously with the backscatter data. At nadir sigma deg of milo correlated highly, r = 0.96, with soil moisture in the milo field at 8.6 GHz but decreased to a value of r = 0.78 at a frequency of 17.0 GHz. Correlation studies of the variations of sigma deg with soil moisture in the soybean fields were not possible due to a lack of a meaningful soil moisture dynamic range. At the larger angles of incidence, however, sigma deg of soybeans did appear to be dependent on precipitation. It is suggested this phenomenon was caused by the rain altering plant geometry. In general sigma deg of both milo and soybeans had a relatively small dynamic range at the higher angles of incidence and showed no significant dependence on the measured crop parameters.

Bush, T. F.↗
DOE OSTI2012

Autotune E+ Building Energy Models

This paper introduces a novel Autotune methodology under development for calibrating building energy models (BEM). It is aimed at developing an automated BEM tuning methodology that enables models to reproduce measured data such as utility bills, sub-meter, and/or sensor data accurately and robustly by selecting best-match E+ input parameters in a systematic, automated, and repeatable fashion. The approach is applicable to a building retrofit scenario and aims to quantify the trade-offs between tuning accuracy and the minimal amount of ground truth data required to calibrate the model. Autotune will use a suite of machine-learning algorithms developed and run on supercomputers to generate calibration functions. Specifically, the project will begin with a de-tuned model and then perform Monte Carlo simulations on the model by perturbing the uncertain parameters within permitted ranges. Machine learning algorithms will then extract minimal perturbation combinations that result in modeled results that most closely track sensor data. A large database of parametric EnergyPlus (E+) simulations has been made publicly available. Autotune is currently being applied to a heavily instrumented residential building as well as three light commercial buildings in which a de-tuned model is autotuned using faux sensor data from the corresponding target E+ model.

automatic calibration↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
NASA NTRS1977

Determination of ocean wave heights from synthetic aperture radar imagery

A calculation is presented for the cross-correlation of the radar images obtained by processing the same signal data over different portions of the chirp spectrum bandwidth as a function of the center frequency spacings for these portions. This is shown to be proportional to the square of the product of the characteristic function for ocean wave heights and the pupil function describing the chirp spectrum bandwidth used in the processing. Measurements of this function for ocean wave imagery over the coast of Alaska, the North Atlantic, and Monterey Bay, California, and correlation with the significant wave heights reported from ground truth data indicate that the synthetic aperture radar instrument can be used for providing wave height information in addition to the ocean wave imagery.

Jain, A.↗
NASA NTRS1983

Quantile Data Analysis of Image Data

Quantile data analysis and functional statistical inference methods are introduced and applied to provide representations of spectral data which may lead to simple statistical discriminators effective for the estimation of ground truth from satellite spectral measurements. To estimate the ground truth of a pixel, the probability of each possible ground truth is estimated, given observed (estimated) quantile theoretic statistical characteristics of the multispectral image data corresponding to the pixel and its neighboring pixels. A strategy for determining which statistical characteristics discriminate best is described. Results are reported of quantile data analysis of an extensive collection of training files of image data.

Parzen, E.↗
NASA NTRS1987

Sensor-based diagnosis using knowledge of structure and function

A system for fault detection and isolation called LES, developed at the Kennedy Space Center for the Space Shuttle's Launch Processing System, is a well-developed diagnostic system that is simultaneously model-based and sensor-based. This experiment has led to a surprising result: the failure of a sensor can not only be handled in precisely the same way as the failure of any other object, but may present an especially easy case. Classical rule-based diagnostic systems need to find out whether or not their sensors are telling them the truth before they can safely draw inferences from them. By contrast, while LES does treat sensors as a special case, it does so only because there may exist a short cut that allows them to be handled more simply than other objects. LES uses both structural and functional knowledge, and has found cases in which the structural knowledge can be economically replaced by the judicious use of functional relationships; LES' functional relationships are stored in exactly one place, so they must be inverted to determine hypothetical values for possibly faulty objects. The inversion process has been extended to include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗
DOE OSTI2022

A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering

The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-scale dense networks, to reconstruct the missing information in experimental scattering images. In particular, the recovered pixel intensities are evaluated against their corresponding ground-truth values using the mean absolute error and the correlation coefficient metrics. The results demonstrate that the proposed methods achieve better performance than traditional inpainting algorithms such as biharmonic functions. Overall, tunable U-Net and mixed-scale dense network architectures achieved the best reconstruction performance among all the tested algorithms, with correlation coefficient scores greater than 0.9980.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1972

Topological solution of bilateral switching networks

Topological method uses the eye as pattern detector to trace path of transmission on truth table. Pathway selection is continually supervised by logician, allowing him to seek planar iterative solution desirable for fabrication of monolithic circuits. Method applies to parity generators, multiple output functions, full adders, and bit comparators.

Mazer, L.↗
NASA NTRS1992

First results from analysis of coordinated AVIRIS, TIMS, and ISM (French) data for the Ronda (Spain) and Beni Bousera (Morocco) peridotites

Ultramafic rocks are relatively rare at the Earth's surface but constitute the vast majority of the Earth by volume. Exposures of ultramafic bodies are therefore crucial for deducing many important processes that occur in the Earth's mantle. An important science question regarding the spatial distribution, abundance, and composition of mafic minerals in ultramafic bodies that can be examined with advanced sensor data is the melting process. When a lherzolite melts, clinopyroxene (cpx) melts first and therefore variations in the modal amount of cpx remaining in the mantle are a reflection of the amount of fractional melting that has occurred. Fe goes preferentially into the melt during melting but a 20 percent batch melting (i.e. closed system) acquires less Fe relative to 20 percent fractional melting (i.e. open system). Since the strength and wavelength of diagnostic absorptions is a strong function of Fe content, it is possible to make maps of the variation in Fe:Mg ratios which can be related to the general melting process. Accurate ground-truth information about local mineralogy provides internal calibration and consistency checks. Investigations using imaging spectrometer are very complementary to field studies because advanced sensor data can provide a synoptic view of modal mineralogy and chemical composition whereas field studies focus on detailed characterization of local areas. Two excellent exposures of ultramafic lithologies are being investigated with visible to mid-infrared imaging spectrometer data: the Ronda peridotite near Ronda, Spain and the Beni Bousera ophiolitic fragment in northern Morocco. Although separated by the Alboran Sea, these bodies are thought to be related and represent fertile sub-continental mantle. The Ronda peridotite is predominantly spinel lherzolite but grades into harzburgite and shows considerable variation in major and trace element compositions. Mafic layering and dykes (i.e. olivine gabbro) are also observed. This indicates some sections of the peridotite have experienced greater degrees of partial melting. The Beni Bousera peridotite also contains mafic layers and dykes and grades into harzburgite representing similar fundamental shifts in the bulk chemistry of this ultramafic body probably related to an episode of partial melting. The specific mode of emplacement of these bodies is controversial and important for understanding the tectonic evolution of this region. Our investigations are not necessarily designed to help resolve this controversy. Rather, these exposures provide excellent and unusual examples of fertile mantle which have undergone variable degrees of partial melting.

Mustard, J. F.↗
DOE OSTI2024

Machine learning based unfolding of x-ray spectra from filter stack spectrometer data

We demonstrate the application of neural networks to perform x-ray spectra unfolding from data collected by filter stack spectrometers. A filter stack spectrometer consists of a series of filter-detector pairs, where the detectors behind each filter measure the energy deposition through each layer as photo-stimulated luminescence (PSL). The network is trained on synthetic data, assuming x-rays of energies < 1 MeV and of two different distribution functions (Maxwellian and Gaussian) and the corresponding measured PSL values obtained from five different filter stack spectrometer designs. Predicted unfolds of single distributions are near identical reproductions of the ground truth spectra, with differences in the values lower than 20% at the higher energy end in some cases. The neural network has also demonstrated robustness to experimental measurement errors of < 5% and some capability of performing unfolds for linear combinations of the two distributions without previous training. The network can perform unfolds at rates > 1 Hz, ideal for application to some high-repetition-rate systems.

47 OTHER INSTRUMENTATION↗