SEARCH · Engineering Papers

Results for “Automatic Data Processing”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗

DOE OSTI2017

Build and Execute Environment

At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.

Guan, Qiang↗

DOE OSTI2017

Build and Execute Environment

Guan, Qiang↗

DOE OSTI2014

WE-D-9A-01: A Novel Mesh-Based Deformable Surface-Contour Registration

Purpose: Initial guess is vital for 3D-2D deformable image registration (DIR) while dealing with large deformations for adaptive radiation therapy. A fast procedure has been developed to deform body surface to match 2D body contour on projections. This surface-contour DIR will provide an initial deformation for further complete 3D DIR or image reconstruction. Methods: Both planning CT images and come-beam CT (CBCT) projections are preprocessed to create 0–1 binary mask. Then the body surface and CBCT projection body contours are extracted by Canny edge detector. A finite element modeling system was developed to automatically generate adaptive meshes based on the image surface. After that, the projections of the CT surface voxels are computed and compared with corresponding 2D projection contours from CBCT scans. As a result, the displacement vector field (DVF) on mesh vertices around the surface was optimized iteratively until the shortest Euclidean distance between the pixels on the projections of the deformed CT surface and the corresponding CBCT projection contour is minimized. With the help of the tetrahedral meshes, we can smoothly diffuse the deformation from the surface into the interior of the volume. Finally, the deformed CT images are obtained by the optimal DVF applied on the original planning CT images. Results: The accuracy of the surface-contour registration is evaluated by 3D normalized cross correlation increased from 0.9176 to 0.9957 (sphere-ellipsoid phantom) and from 0.7627 to 0.7919 (H and N cancer patient data). Under the GPU-based implementation, our surface-contour-guided method on H and N cancer patient data takes 8 seconds/iteration, about 7.5 times faster than direct 3D method (60 seconds/iteration), and it needs fewer optimization iterations (30 iterations vs 50 iterations). Conclusion: The proposed surface-contour DIR method can substantially improve both the accuracy and the speed of reconstructing volumetric images, which is helpful for applying in adaptive radiotherapy. This research is supported by CPRIT individual investigator award RP110329.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1992

StarView: The object oriented design of the ST DADS user interface

StarView is the user interface being developed for the Hubble Space Telescope Data Archive and Distribution Service (ST DADS). ST DADS is the data archive for HST observations and a relational database catalog describing the archived data. Users will use StarView to query the catalog and select appropriate datasets for study. StarView sends requests for archived datasets to ST DADS which processes the requests and returns the database to the user. StarView is designed to be a powerful and extensible user interface. Unique features include an internal relational database to navigate query results, a form definition language that will work with both CRT and X interfaces, a data definition language that will allow StarView to work with any relational database, and the ability to generate adhoc queries without requiring the user to understand the structure of the ST DADS catalog. Ultimately, StarView will allow the user to refine queries in the local database for improved performance and merge in data from external sources for correlation with other query results. The user will be able to create a query from single or multiple forms, merging the selected attributes into a single query. Arbitrary selection of attributes for querying is supported. The user will be able to select how query results are viewed. A standard form or table-row format may be used. Navigation capabilities are provided to aid the user in viewing query results. Object oriented analysis and design techniques were used in the design of StarView to support the mechanisms and concepts required to implement these features. One such mechanism is the Model-View-Controller (MVC) paradigm. The MVC allows the user to have multiple views of the underlying database, while providing a consistent mechanism for interaction regardless of the view. This approach supports both CRT and X interfaces while providing a common mode of user interaction. Another powerful abstraction is the concept of a Query Model. This concept allows a single query to be built form a single or multiple forms before it is submitted to ST DADS. Supporting this concept is the adhoc query generator which allows the user to select and qualify an indeterminate number attributes from the database. The user does not need any knowledge of how the joins across various tables are to be resolved. The adhoc generator calculates the joins automatically and generates the correct SQL query.

Williams, J. D.↗

NASA NTRSDate not supplied

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗

DOE OSTI2022

Automatic detection of low surface brightness galaxies from Sloan Digital Sky Survey images

ABSTRACT Low surface brightness (LSB) galaxies are galaxies with central surface brightness fainter than the night sky. Due to the faint nature of LSB galaxies and the comparable sky background, it is difficult to search LSB galaxies automatically and efficiently from large sky survey. In this study, we established the low surface brightness galaxies autodetect (LSBG-AD) model, which is a data-driven model for end-to-end detection of LSB galaxies from Sloan Digital Sky Survey (SDSS) images. Object-detection techniques based on deep learning are applied to the SDSS field images to identify LSB galaxies and estimate their coordinates at the same time. Applying LSBG-AD to 1120 SDSS images, we detected 1197 LSB galaxy candidates, of which 1081 samples are already known and 116 samples are newly found candidates. The B-band central surface brightness of the candidates searched by the model ranges from 22 to 24 mag arcsec−2, quite consistent with the surface brightness distribution of the standard sample. A total of 96.46 per cent of LSB galaxy candidates have an axial ratio (b/a) greater than 0.3, and 92.04 per cent of them have $fracDev\_r$ < 0.4, which is also consistent with the standard sample. The results show that the LSBG-AD model learns the features of LSB galaxies of the training samples well, and can be used to search LSB galaxies without using photometric parameters. Next, this method will be used to develop efficient algorithms to detect LSB galaxies from massive images of the next-generation observatories.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Innovative Patient Room Lighting System with Integrated Spectrally Adaptive Control

In December of 2013, the U.S. Department of Energy’s SSL R&D Program released a Funding Opportunity Announcement (FOA), that for the first time, contained opportunities for comprehensive application-specific system development. The FOA included opportunities for two applications, one of which was a Patient Room. Philips Lighting Research North America, submitted a proposal for the Patient Room application, and was selected for the complete project award. The award amount was for $497,127, with a Philips Research co-funding commitment 165,709 dollars. The total project value was 662,836 dollars. This project sought to redefine lighting for the patient room application. The goal was to deliver an innovative LED patient suite (patient room and bathroom) lighting system solution that was 40% more energy-efficient than traditional fluorescent incumbent technologies, and would meet all the visual and non-visual needs of patients, caregivers and visitors, and improve the patient experience. State-of-the-art multichannel LED platforms and control technologies that would provide spectral tuning and become part of an intelligent, connected lighting system drove the solution. The project was scoped into four main task areas that included a) System Concept Creation, b) Identification of the Luminaire Portfolio, c) Development of the Connected Lighting Infrastructure, and d) System Performance Validation. Each of the four main tasks were completed and validated extensively over the course the 2 ½ year project. The system concept was created by first developing a lighting design that demonstrated best practices for patient room lighting – illuminance and uniformity for task performance, reduced glare, and convenient controls, in addition to giving patients control over the lighting in their environment. A framework was defined to deliver circadian support via software behaviors. Through that process luminaires were identified from the Philips portfolio that were adaptable – by their form, dimensions, and optical materials – to mix multicolor LED platforms uniformly and deliver target design lumen levels. The Blue Sky luminaire was selected for the patient bed area to give the illusion of skylight while providing white light on the patient bed. Luminaires used existing 2-channel tunable white LED boards, and newly developed 4-channel LED boards. Red-Orange, Blue, Green, and Blue-shifted Yellow LED chips were selected based on spectral characteristics and their ability to produce high quality white light. 4-channel Power over Ethernet (PoE) drivers were developed and firmware written so they would communicate with both 2- and 4-channel boards. These components formed the backbone of the connected lighting infrastructure. Software, flexible and nuanced in its complexity, was written to set behaviors for myriad lighting scenes in the room throughout the 24 hour day – and all could be overridden by manual controls. This included a dynamic tunable white program, three color changing automatic programs that simulated degrees of sunrise to sunset palettes, and an amber night lighting system that offered visual cues for postural stability to minimize the risk of falls. All programs were carefully designed to provide visual comfort for all occupants, support critical task performance for staff, and to support the patient’s 24hr rhythms. A full scale mockup room was constructed in the Philips Cambridge Lab. The lighting system was installed, tested and functionality demonstrated to ensure smooth operation of system components – luminaires, drivers, PoE switches, wall controls, patient remote, and daylight and occupancy sensors. How did the system perform? It met visual criteria, confirmed by calculations, simulations and measurements in the field. It met non-visual criteria, confirmed by setting circadian stimulus (CS) targets and performing calculations using the calculator developed by the Lighting Research Center. Finally, human factors validation studies were conducted to gain insight from real end users in the healthcare profession; surveys were administered, data analyzed, and audio comments captured. The general consensus was positive, with requests to pilot the system in their hospitals. The importance of the research completed under this grant is that it allowed the exploration and development of a unique lighting system, one that would deliver a blend of visual and non-visual criteria in patient room design for today’s healthcare environment. The research investigated the area of multichannel LED technology, multichannel Power over Ethernet (PoE) drivers and their integration with automatic and manual controls as a system – uncovering and meeting challenges along the way. It married visual needs of patients and staff with support for 24 hour rhythms, placing value on the wellbeing of the patient – while successfully saving energy over incumbent technologies. Indications are that the market is ready and willing to invest – multiple healthcare facilities are in line to pilot this system, recognizing its value beyond energy to patient and staff well-being. Its value to the public can best be expressed by a patient support coordinator who, after spending several hours in the room being immersed in the lighting, analyzing all its features, commented: “This re-writes lighting for healthcare”.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm

The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applications. Modern phase retrieval approaches usually rely on gradient descent methods in a nonlinear minimization framework. Calculating closed-form gradients for use in these methods is tedious work, and formulating second order derivatives is even more laborious. Additionally, second order techniques often require the storage and inversion of large matrices of partial derivatives, with memory requirements that can be prohibitive for data-rich imaging modalities. We use a reverse-mode automatic differentiation (AD) framework to implement an efficient matrix-free version of the Levenberg-Marquardt (LM) algorithm, a longstanding method that finds popular use in nonlinear least-square minimization problems but which has seen little use in phase retrieval. Furthermore, we extend the basic LM algorithm so that it can be applied for more general constrained optimization problems (including phase retrieval problems) beyond just the least-square applications. Since we use AD, we only need to specify the physics-based forward model for a specific imaging application; the first and second-order derivative terms are calculated automatically through matrix-vector products, without explicitly forming the large Jacobian or Gauss-Newton matrices typically required for the LM method. We demonstrate that this algorithm can be used to solve both the unconstrained ptychographic object retrieval problem and the constrained “blind” ptychographic object and probe retrieval problems, under the popular Gaussian noise model as well as the Poisson noise model. We compare this algorithm to state-of-the-art first order ptychographic reconstruction methods to demonstrate empirically that this method outperforms best-in-class first-order methods: it provides excellent convergence guarantees with (in many cases) a superlinear rate of convergence, all with a computational cost comparable to, or lower than, the tested first-order algorithms.

36 MATERIALS SCIENCE↗

NASA NTRS2010

Efficient Web Services Policy Combination

Large-scale Web security systems usually involve cooperation between domains with non-identical policies. The network management and Web communication software used by the different organizations presents a stumbling block. Many of the tools used by the various divisions do not have the ability to communicate network management data with each other. At best, this means that manual human intervention into the communication protocols used at various network routers and endpoints is required. Developing practical, sound, and automated ways to compose policies to bridge these differences is a long-standing problem. One of the key subtleties is the need to deal with inconsistencies and defaults where one organization proposes a rule on a particular feature, and another has a different rule or expresses no rule. A general approach is to assign priorities to rules and observe the rules with the highest priorities when there are conflicts. The present methods have inherent inefficiency, which heavily restrict their practical applications. A new, efficient algorithm combines policies utilized for Web services. The method is based on an algorithm that allows an automatic and scalable composition of security policies between multiple organizations. It is based on defeasible policy composition, a promising approach for finding conflicts and resolving priorities between rules. In the general case, policy negotiation is an intractable problem. A promising method, suggested in the literature, is when policies are represented in defeasible logic, and composition is based on rules for non-monotonic inference. In this system, policy writers construct metapolicies describing both the policy that they wish to enforce and annotations describing their composition preferences. These annotations can indicate whether certain policy assertions are required by the policy writer or, if not, under what circumstances the policy writer is willing to compromise and allow other assertions to take precedence. Meta-policies are specified in defeasible logic, a computationally efficient non-monotonic logic developed to model human reasoning. One drawback of this method is that at one point the algorithm starts an exhaustive search of all subsets of the set of conclusions of a defeasible theory. Although the propositional defeasible logic has linear complexity, the set of conclusions here may be large, especially in real-life practical cases. This phenomenon leads to an inefficient exponential explosion of complexity. The current process of getting a Web security policy from combination of two meta-policies consists of two steps. The first is generating a new meta-policy that is a composition of the input meta-policies, and the second is mapping the meta-policy onto a security policy. The new algorithm avoids the exhaustive search in the current algorithm, and provides a security policy that matches all requirements of the involved metapolicies.

Vatan, Farrokh↗

NASA NTRSDate not supplied

Trace Oxygen Measurements of Asteroid Sample Storage Desiccators

The Astromaterials Curation facility at the NASA Johnson Space Center is currently curating more than 120 g of carbonaceous asteroid Bennu material as well as over 500 mg of asteroid Ryugu [1 and 2]. These astromaterials are stored in isolating desiccators and gloveboxes under a continuous purge of pure (<1 ppm O 2 ) gaseous nitrogen. The oxygen and moisture concentrations in our OSIRIS-REx sample processing gloveboxes are continuously monitored via integrated sensors; however, our sample storage desiccators lack integrated oxygen and humidity sensors. In previous studies, we used PreSens Fibox 4 trace oxygen meters and optochemical PSt9 spot sensors to measure the oxygen concentrations in candidate asteroid sample containers that had been sealed in nitrogen; we determined that Eagle stainless steel containers inhibit the ingress of external oxygen for several weeks [3]. This optochemical sensor technology allowed us to take precise, contactless measurements within a trace range of 0 to 200 ppmv O 2 . The effectiveness of the trace oxygen sensors in our container experiments inspired us to utilize them to assess the performance of our desiccators that previously lacked trace oxygen monitoring. In this study, our goal was to determine the quality of the nitrogen purge in the isolating desiccator under normal operating conditions by measuring the trace oxygen content. Utilizing optochemical sensor technology, we determined how long the oxygen concentration takes to reach an equilibrium in the desiccator; that is, determine the rate at which the oxygen diffusion into the desiccator equals the rate at which oxygen diffuses out of the desiccator via N2 purge. Additionally, we wanted to determine the oxygen concentration at this equilibrium, the state in which our desiccators are in during normal operating conditions. We tested a custom three chamber desiccator manufactured by Germfree using a PSt9 trace oxygen sensor spot that was mounted into a ¼” National Pipe Tapered (NPT) metal flow-through cell and attached it to the desiccator exhaust. The desiccator consists of top, middle, and bottom isolating chambers. The top chamber door was opened for several minutes to simulate a sample exchange, it was sealed, and then purged ~15 Standard Cubic Feet per Hour (SCFH). Oxygen measurements were automatically recorded via the Fibox 4 trace oxygen meter in 5-minute intervals over the course of a 24-hour period. Our results indicate the desiccator reached an equilibrium value of 10-15 ppm O 2 after ~5 hours (Fig. 1). This data allows us to explore standards for purging and exchange protocols that can be applied to similar types of desiccators in Hayabusa2, OSIRIS-REx, and for sample return collections. The assessment of the internal gaseous compositions of desiccators also allows us to share with the community the N 2 environment in which many of our asteroid samples and hardware are securely curated. Future measurements will include other nitrogen flow rates and measuring the trace oxygen concentration as a function of time for the levels of the previous commercial desiccator in which the Hayabusa2 sample collection was stored. We will also analyze how long the desiccators hold N2 after being disconnected from their N2 source, an extended measurement for sample security reassurance.

Curation↗

DOE OSTI2014

The influence of respiratory motion on CT image volume definition

Purpose: Radiotherapy treatments are based on geometric and density information acquired from patient CT scans. It is well established that breathing motion during scan acquisition induces motion artifacts in CT images, which can alter the size, shape, and density of a patient's anatomy. The aim of this work is to examine and evaluate the impact of breathing motion on multislice CT imaging with respiratory synchronization (4DCT) and without it (3DCT). Methods: A specific phantom with a movable insert was used. Static and dynamic phantom acquisitions were obtained with a multislice CT. Four sinusoidal breath patterns were simulated to move known geometric structures longitudinally. Respiratory synchronized acquisitions (4DCT) were performed to generate images during inhale, intermediate, and exhale phases using prospective and retrospective techniques. Static phantom data were acquired in helical and sequential mode to define a baseline for each type of respiratory 4DCT technique. Taking into account the fact that respiratory 4DCT is not always available, 3DCT helical image studies were also acquired for several CT rotation periods. To study breath and acquisition coupling when respiratory 4DCT was not performed, the beginning of the CT image acquisition was matched with inhale, intermediate, or exhale respiratory phases, for each breath pattern. Other coupling scenarios were evaluated by simulating different phantom and CT acquisition parameters. Motion induced variations in shape and density were quantified by automatic threshold volume generation and Dice similarity coefficient calculation. The structure mass center positions were also determined to make a comparison with their theoretical expected position. Results: 4DCT acquisitions provided volume and position accuracies within ±3% and ±2 mm for structure dimensions >2 cm, breath amplitude ≤15 mm, and breath period ≥3 s. The smallest object (1 cm diameter) exceeded 5% volume variation for the breath patterns of higher frequency and amplitude motion. Larger volume differences (>10%) and inconsistencies between the relative positions of objects were detected in image studies acquired without respiratory control. Increasing the 3DCT rotation period caused a higher distortion in structures without obtaining their envelope. Simulated data showed that the slice acquisition time should be at least twice the breath period to average object movement. Conclusions: Respiratory 4DCT images provide accurate volume and position of organs affected by breath motion detecting higher volume discrepancies as amplitude length or breath frequency are increased. For 3DCT acquisitions, a CT should be considered slow enough to include lesion envelope as long as the slice acquisition time exceeds twice the breathing period. If this requirement cannot be satisfied, a fast CT (along with breath-hold inhale and exhale CTs to estimate roughly the ITV) is recommended in order to minimize structure distortion. Even with an awareness of a patient's respiratory cycle, its coupling with 3DCT acquisition cannot be predicted since patient anatomy is not accurately known.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

Automating linear accelerator quality assurance

Purpose: The purpose of this study was 2-fold. One purpose was to develop an automated, streamlined quality assurance (QA) program for use by multiple centers. The second purpose was to evaluate machine performance over time for multiple centers using linear accelerator (Linac) log files and electronic portal images. The authors sought to evaluate variations in Linac performance to establish as a reference for other centers. Methods: The authors developed analytical software tools for a QA program using both log files and electronic portal imaging device (EPID) measurements. The first tool is a general analysis tool which can read and visually represent data in the log file. This tool, which can be used to automatically analyze patient treatment or QA log files, examines the files for Linac deviations which exceed thresholds. The second set of tools consists of a test suite of QA fields, a standard phantom, and software to collect information from the log files on deviations from the expected values. The test suite was designed to focus on the mechanical tests of the Linac to include jaw, MLC, and collimator positions during static, IMRT, and volumetric modulated arc therapy delivery. A consortium of eight institutions delivered the test suite at monthly or weekly intervals on each Linac using a standard phantom. The behavior of various components was analyzed for eight TrueBeam Linacs. Results: For the EPID and trajectory log file analysis, all observed deviations which exceeded established thresholds for Linac behavior resulted in a beam hold off. In the absence of an interlock-triggering event, the maximum observed log file deviations between the expected and actual component positions (such as MLC leaves) varied from less than 1% to 26% of published tolerance thresholds. The maximum and standard deviations of the variations due to gantry sag, collimator angle, jaw position, and MLC positions are presented. Gantry sag among Linacs was 0.336 ± 0.072 mm. The standard deviation in MLC position, as determined by EPID measurements, across the consortium was 0.33 mm for IMRT fields. With respect to the log files, the deviations between expected and actual positions for parameters were small (<0.12 mm) for all Linacs. Considering both log files and EPID measurements, all parameters were well within published tolerance values. Variations in collimator angle, MLC position, and gantry sag were also evaluated for all Linacs. Conclusions: The performance of the TrueBeam Linac model was shown to be consistent based on automated analysis of trajectory log files and EPID images acquired during delivery of a standardized test suite. The results can be compared directly to tolerance thresholds. In addition, sharing of results from standard tests across institutions can facilitate the identification of QA process and Linac changes. These reference values are presented along with the standard deviation for common tests so that the test suite can be used by other centers to evaluate their Linac performance against those in this consortium.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

Foundations of Feature Selection and Classification for Non-Gaussian Distributed Targets

This report describes the author’s research toward creating algorithms for selecting useful statistical features in pattern/target classification problems in which the features are non-Gaussian distributed. In engineering practice, it is common to either (1) Not perform any feature selection procedure, or (2) Use a feature selection algorithm that assumes the features are Gaussian distributed. This process can be far from optimal if the data are actually non-Gaussian, as they frequently are in practice. This research has the goal of mitigating that problem by creating a useful algorithm that can be used in practice. The approach is to focus on the performance indices used in common feature selection algorithms, such as Branch and Bound algorithms and the Sequential Forward Selection Algorithm. Ordinarily, the performance index used to measure the class separation in feature space involves assuming the data are Gaussian and deriving tractable performance indices that use closed form equations that represent the probability density functions of the class data. The advantage of this approach is that it produces feature selection algorithms that have low computational complexity and do not require knowledge of the actual data densities. The disadvantage is that these algorithms may not perform reasonably when the data are non-Gaussian, as they commonly are in practice. This research examines the use of information-theoretic class separability measures that can deal with the non-Gaussian case. In particular, this work shows that the Hellinger Distance (a divergence measure), has very desirable mathematical properties and can be useful for feature selection. The work in this paper employs a multivariate kernel density estimator along with the Hellinger Distance and an optimal subset selection algorithm to do feature selection. This report (1) Defines the classification and feature selection problems, (2) Describes the continuous variable Hellinger distance in one dimension and discusses its mathematical properties in comparison with other distance measures, (3) Develops the discrete variable Hellinger distance expression for one and two dimensions, and shows that the discrete Hellinger distance for multiple dimensions is a straightforward extension, and (4) Presents experimental density estimation results using a new MATLAB implementation of a multivariate kernel density estimator. The draft of this report served as a starting point for Ensign Matthew Wilder’s MSEE thesis work at the Naval Postgraduate School (NPS) in 2010 and 2011. Ensign Wilder completed his thesis and graduated from NPS in June 2011 (M. J. Wilder, “Automatic Target Recognition: Statistical Feature Selection of Non-Gaussian Distributed Target Classes,” MSEE Thesis, Naval Postgraduate School, Thesis Advisor: Grace A. Clark, Second Reader: Monique P. Fargues, June 2011). In the thesis, Ensign Wilder created implementations of the Branch and Bound and Sequential Feature Selection algorithms, extended the multivariate kernel density estimator code, and evaluated the performance of Hellinger Distance-based feature selection algorithms using both simulated data and data from a real-world benchmark data set. The new algorithm was shown to be very effective for both Gaussian and non-Gaussian data sets. The advantages gained for non-Gaussian data come at the cost of increased computational complexity. Using a laptop computer for practical problems, we generally use initial feature vectors containing no more than about ten or twelve features. Proposed future research lies in creating faster kernel density estimator algorithms that would allow for the use of higher dimensional data.

42 ENGINEERING↗

DOE OSTI2016

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

Purpose: Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. Methods: Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. Results: The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within {approx}200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of {approx}75 mm and 370 mm, respectively). The median TRE within {approx}200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p= 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). Conclusions: Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Resolution Versus Error for Computational Electron Microscopy

Images that are collected via scanning transmission electron microscopy (STEM) can be undersampled to avoid damage to the specimen while maintaining resolution [1, 2]. We have used BPFA to impute missing data and reduce noise [3]. The reconstruction is typically evaluated using the peak signal-to-noise ratio (PSNR). This measure is too conservative for STEM images and we propose that the Fourier ring correlation (FRC) is used instead to evaluate the reconstruction. We are not concerned with exact reconstruction of the truth image, and therefore PSNR is a conservative estimation of the quality of the reconstruction. Instead, we are concerned with the visual resolution of the image and whether atoms can be distinguished. We have evaluated the reconstruction of a simulated STEM image using the FRC and compared the results with the PSNR measurements. The FRC captures the resolution of the image and is not affected by a large MSE if the atom peaks are still distinguishable. The noisy and reconstructed images are shown in Figure 1. The simulated STEM image was sampled at 100%, 80%, 40%, and 20% of the original pixels to simulate an undersampled scan. The reconstruction was done using BPFA with a patch size of 10 x 10 and no overlapping patches. Not having overlapping patches produces inferior results but they are still acceptable. The dictionary size is 64 and 30 iterations were completed during each reconstruction. The 100% image was denoised instead of reconstructed. Poisson noise was applied to the simulated image with λ values of 500, 50, and 5 to simulate lower imaging dose. The original simulated STEM image was also included in our calculations and was generated using a dose of 1000. The simulated STEM image is 100 by 100 pixels and has essentially no high frequency components. The image reconstruction tends to smooth the data, also resulting in no high frequency components. This causes the FRC of the two images to be large at higher resolutions and may be misleading. For this reason, the BPFA has no overlap to avoid excessive smoothing. Moreover, the resolution of the simulated image is approximately 9.2 (1/nm), so we only look that far in the frequency domain when performing FRC. If the FRC curve does not crossover the threshold, a resolution value of 9.2 is used. We emphasize that our reported results are conservative. The FRC and PSNR values using the ground truth and the reconstructed images are shown in Tables 1 and 2. The left side show the metrics without using BPFA (missing pixels) and the right side show the metrics after using BPFA. When we did not use BPFA, the Fourier transform was estimated [4]. Some threshold curves have been studied [5], but they are derived for additive noise models. Since we have a Poisson noise model, we have used the more conservative threshold of 0.5 for our calculations. Ten images were used to construct each cell of tables in the form of the mean of the metric plus or minus its standard deviation. As expected, the PSNR dies off much quicker than the FRC values for the same image. For the 100% and 80% sampled versions of the truth image, the resolution only dies off when the dose is 5. However, the PSNR dies off rapidly as the dose is reduced. For the 1000, 500, and 50 dose images, the FRC is the maximum, or close, until we undersample at 20%. The PSNR for these values tapers down as we get into the bottom right hand corner of the table, even though the resolution remains high. Overall, we find that undersampled images can be reconstructed to acceptable resolution even when the dose per pixel is also reduced[6]. References: [1]A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2]A Stevens, L Kovarik, P Abellan et al. Advanced Structural and Chemical Imaging 1(1), (2015), pp. 1. [3]M Zhou, H Chen, J Paisley et al. Image Processing, IEEE Transactions on 21(1), (2012), pp. 130. [4]V. Y. Liepin’sh. Automatic control and computer sciences 30(3), (1996), pp. 20.

Luzi, Lorenzo↗