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At least 595 records · Page 33

Modeling and Simulation of the Angel Upper Limb Offload Device: Branching Into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

Modeling and Simulation of The Angel Upper Limb Offload Device: Branching into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

Survey geometry and the internal consistency of recent cosmic shear measurements

We explore the impact of an update to the typical approximation for the shape noise term in the analytic covariance matrix for cosmic shear experiments that assumes the absence of survey boundary and mask effects. We present an exact expression for the number of galaxy pairs in this term based on the survey mask, which leads to more than a factor of three increase in the shape noise on the largest measured scales for the Kilo-Degree Survey (KiDS-450) real-space cosmic shear data. We compare the result of this analytic expression to several alternative methods for measuring the shape noise from the data and find excellent agreement. This update to the covariance resolves any internal model tension evidenced by the previously large cosmological best-fitting χ 2 for the KiDS-450 cosmic shear data. The best-fitting χ 2 is reduced from 161 to 121 for 118 degrees of freedom. We also apply a correction to how the multiplicative shear calibration uncertainty is included in the covariance. This change shifts the inferred amplitude of the correlation function to higher values. In conclusion, we find that this improves agreement of the KiDS-450 cosmic shear results with Dark Energy Survey Year 1 and Planck results.

79 ASTRONOMY AND ASTROPHYSICS↗

Survey geometry and the internal consistency of recent cosmic shear measurements

Here, we explore the impact of an update to the typical approximation for the shape noise term in the analytic covariance matrix for cosmic shear experiments that assumes the absence of survey boundary and mask effects. We present an exact expression for the number of galaxy pairs in this term based on the the survey mask, which leads to more than a factor of three increase in the shape noise on the largest measured scales for the Kilo-Degree Survey (KIDS-450) real-space cosmic shear data. We compare the result of this analytic expression to several alternative methods for measuring the shape noise from the data and find excellent agreement. This update to the covariance resolves any internal model tension evidenced by the previously large cosmological best-fit $\chi^2$ for the KiDS-450 cosmic shear data. The best-fit $\chi^2$ is reduced from 161 to 121 for 118 degrees of freedom. We also apply a correction to how the multiplicative shear calibration uncertainty is included in the covariance. This change, along with a previously known update to the reported effective angular values of the data vector, jointly shift the inferred amplitude of the correlation function to higher values. Lastly, we find that this improves agreement of the KiDS-450 cosmic shear results with Dark Energy Survey Year 1 and Planck results.

79 ASTRONOMY AND ASTROPHYSICS↗

Anomalous krypton in the Allende meteorite

The reported investigation provides important new data for the heavy noble gases, especially Kr, in the Allende meteorite. The data are used to criticize the original model of Lewis et al. (1975) based on the noble gas data of these researchers. The conclusions reached in the investigation support alternative models which have been mainly based on Xe data by Lewis et al. (1975, 1977). Because of the relatively high noble gas abundances in the separates studied, disturbance from nuclear effects occurring in situ such as spallation and neutron capture is insignificant, offering an opportunity to study primordial Ar, Kr, and Xe. The isotopic and abundance data obtained from the samples largely confirm the noble gas results of Lewis et al. (1975, 1977) where isotopic correlations agree with the correlations of the considered samples. It is found that both Kr and Xe data are consistent with a two component mixture of 'ordinary' as well as 'anomalous' planetary gases.

Frick, U.↗

Potential of adult mammalian lumbosacral spinal cord to execute and acquire improved locomotion in the absence of supraspinal input

The neural circuitry of the lumbar spinal cord can generate alternating extension and flexion of the hindlimbs. The hindlimbs of adult cats with complete transection of the spinal cord at a low thoracic level (T12-T13) can perform full weight-supporting locomotion on a treadmill belt moving at a range of speeds. Some limitations in the locomotor capacity can be associated with a deficit in the recruitment level of the fast extensors during the stance phase and the flexors during the swing phase of a step cycle. The level of locomotor performance, however, can be enhanced by daily training on a treadmill while emphasizing full weight-support stepping and by providing appropriately timed sensory stimulation, loading, and/or pharmacologic stimulation of the hindlimb neuromuscular apparatus. Furthermore, there appears to be an interactive effect of these interventions. For example, the maximum treadmill speed that a spinal adult cat can attain and maintain is significantly improved with daily full weight-supporting treadmill training, but progressive recruitment of fast extensors becomes apparent only when the hindlimbs are loaded by gently pulling down on the tail during the stepping. Stimulation of the sural nerve at the initiation of the flexion phase of the step cycle can likewise markedly improve the locomotor capability. Administration of clonidine, in particular in combination with an elevated load, resulted in the most distinct and consistent alternating bursts of electromyographic activity during spinal stepping. These data indicate that the spinal cord has the ability to execute alternating activation of the extensor and flexor musculature of the hindlimbs (stepping) and that this ability can be improved by several interventions such as training, sensory stimulation, and use of some pharmacologic agents. Thus, it appears that the spinal cord, without supraspinal input, is highly plastic and has the potential to "learn," that is, to acquire and improve its ability to execute full weight-supporting locomotion on a treadmill belt.

NASA Discipline Musculoskeletal↗

Galileon gravity in light of ISW, CMB, BAO and H {sub 0} data

Cosmological models with Galileon gravity are an alternative to the standard ΛCDM paradigm with testable predictions at the level of its self-accelerating solutions for the expansion history, as well as large-scale structure formation. Here, we place constraints on the full parameter space of these models using data from the cosmic microwave background (CMB) (including lensing), baryonic acoustic oscillations (BAO) and the Integrated Sachs-Wolfe (ISW) effect. We pay special attention to the ISW effect for which we use the cross-spectra, C {sub ℓ}{sup Tg}, of CMB temperature maps and foreground galaxies from the WISE survey. The sign of C {sub ℓ}{sup Tg} is set by the time evolution of the lensing potential in the redshift range of the galaxy sample: it is positive if the potential decays (like in ΛCDM), negative if it deepens. We constrain three subsets of Galileon gravity separately known as the Cubic, Quartic and Quintic Galileons. The cubic Galileon model predicts a negative C {sub ℓ}{sup Tg} and exhibits a 7.8σ tension with the data, which effectively rules it out. For the quartic and quintic models the ISW data also rule out a significant portion of the parameter space but permit regions where the goodness-of-fit is comparable to ΛCDM. The data prefers a non zero sum of the neutrino masses (∑ m {sub ν} ≈ 0.5eV) with ∼ 5σ significance in these models. The best-fitting models have values of H {sub 0} consistent with local determinations, thereby avoiding the tension that exists in ΛCDM. We also identify and discuss a ∼ 2σ tension that Galileon gravity exhibits with recent BAO measurements. Our analysis shows overall that Galileon cosmologies cannot be ruled out by current data but future lensing, BAO and ISW data hold strong potential to do so.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance measurements of a data link protocol

The end-to-end performance of a program implementing IEEE Std 802.2 logical link control protocol, which provides virtual circuit and datagram service and which constitutes the top sublayer of the data link layer of the reference model for Local Area Networks is studied. The measurements of relative execution times of various functions required in transferring data, over virtual circuits or as datagrams, showed that most of the program execution time is spent in a few relatively low-level functions. One of these functions performs block movement of data in memory, and two other functions provide access to various queues. Based on this result, two alternative versions of the program which move data efficiently were written and measured. In this paper the results of the study are reported and their impact on designing hardware and software systems for a network interface are discussed.

Kanakia, Hemant↗

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

Abstract Subsurface flow model calibration involves many more unknowns than measurements, leading to ill‐posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher‐order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., ‐SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient‐based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Khaninezhad, Mohammad‐Reza↗

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes

For many simulation models, it can be prohibitively expensive or physically infeasible to obtain a complete set of experimental data to calibrate model parameters. In such cases, one can alternatively employ validated higher-fidelity codes to generate simulated data, which can be used to calibrate the lower-fidelity code. In this paper, we employ an information-theoretic framework to determine the reduction in parameter uncertainty that is obtained by evaluating the high-fidelity code at a specific set of design conditions. These conditions are chosen sequentially, based on the amount of information that they contribute to the low-fidelity model parameters. The goal is to employ Bayesian experimental design techniques to minimize the number of high-fidelity code evaluations required to accurately calibrate the low-fidelity model. We illustrate the performance of this framework using heat and diffusion examples, a 1-D kinetic neutron diffusion equation, and a particle transport model, and include initial results from the integration of the high-fidelity thermal-hydraulics code Hydra-TH with a low-fidelity exponential model for the friction correlation factor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Interface Tracking Investigation of Geometric Effects on the Bubbly Flow in PWR Subchannels

We report that absorbing heat from the fuel rod surface, water as coolant can undergo subcooled boiling within a pressurized water reactor (PWR) fuel rod bundle. Because of the buoyancy effect, the vapor bubbles generated will then rise along and interact with the subchannel geometries. Reliable prediction of bubble behavior is of immense importance to ensure safe and stable reactor operation. However, given a complex engineering system like a nuclear reactor, it is very challenging (if not impossible) to conduct high-resolution measurements to study bubbly flows under reactor operation conditions. The lack of a fundamental two-phase-flow database is hindering the development of accurate two-phase-flow models required in more advanced reactor designs. In response to this challenge, first-principles–based numerical simulations are emerging as an attractive alternative to produce a complementary data source along with experiments. Leveraged by the unprecedented computing power offered by state-of-the-art supercomputers, direct numerical simulation (DNS), coupled with interface tracking methods, is becoming a practical tool to investigate some of the most challenging engineering flow problems. In the presented research, turbulent bubbly flow is simulated via DNS in single PWR subchannel geometries with auxiliary structures (e.g., supporting spacer grid and mixing vanes). The geometric effects these structures exert on the bubbly flow are studied with both a conventional time-averaging approach and a novel dynamic bubble tracking method. Lastly, the new insights obtained will help inform better two-phase models that can contribute to safer and more efficient nuclear reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

dCache on Steroids - Delegated Storage Solutions

For over a decade, dCache.org has delivered a robust software used at more than 80 Universities and research institutes around the world, allowing these sites to provide reliable storage services for the WLCG experiments as well as many other scientific communities. The flexible architecture of dCache allows running it in a wide variety of configurations and platforms - from a SoC based all-in-one Raspberry-Pi up to hundreds of nodes in a multipetabyte installation. Due to lack of managed storage at the time, dCache implemented data placement, replication and data integrity directly. Today, many alternatives are available: S3, GlusterFS, CEPH and others. While such solutions position themselves as scalable storage systems, they cannot be used by many scientific communities out of the box. The absence of community-accepted authentication and authorization mechanisms, the use of product specific protocols and the lack of namespace are some of the reasons that prevent wide-scale adoption of these alternatives. Most of these limitations are already solved by dCache. By delegating low-level storage management functionality to the above-mentioned new systems and providing the missing layer through dCache, we provide a solution which combines the benefits of both worlds - industry standard storage building blocks with the access protocols and authentication required by scientific communities. In this paper, we focus on CEPH, a popular software for clustered storage that supports file, block and object interfaces. CEPH is often used in modern computing centers, for example as a backend to OpenStack services. We will show prototypes of dCache running with a CEPH backend and discuss the benefits and limitations of such an approach. As a result, we will also outline the roadmap for supporting ‘delegated storage’ within the dCache releases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Using angular two-point correlations to self-calibrate the photometric redshift distributions of DECaLS DR9

Calibrating the redshift distributions of photometric galaxy samples is essential in weak lensing studies. The self-calibration method combines angular auto- and cross-correlations between galaxies in multiple photometric redshift (photo-z) bins to reconstruct the scattering rates matrix between redshift bins. In this paper, we test a recently proposed self-calibration algorithm using the DECaLS Data Release 9 and investigate to what extent the scattering rates are determined. We first mitigate the spurious angular correlations due to imaging systematics by a machine learning based method. We then improve the algorithm for χ 2 minimization and error estimation. Finally, we solve for the scattering matrices, carry out a series of consistency tests, and find reasonable agreements: (1) finer photo-z bins return a high-resolution scattering matrix, and it is broadly consistent with the low-resolution matrix from wider bins; (2) the scattering matrix from the Northern Galactic Cap is almost identical to that from Southern Galactic Cap; (3) the scattering matrices are in reasonable agreement with those constructed from the power spectrum and the weighted spectroscopic subsample. We also evaluate the impact of cosmic magnification. Although it changes little the diagonal elements of the scattering matrix, it affects the off-diagonals significantly. The scattering matrix also shows some dependence on scale cut of input correlations, which may be related to a known numerical degeneracy between certain scattering pairs. In conclusion, this work demonstrates the feasibility of the self-calibration method in real data and provides a practical alternative to calibrate the redshift distributions of photometric samples.

79 ASTRONOMY AND ASTROPHYSICS↗

Reverse Monte Carlo modeling for low-dimensional systems

Reverse Monte Carlo (RMC) is one of the commonly used approaches for modeling total scattering data. However, to extend the capability of the RMC method for refining the structure of nanomaterials, the dimensionality and finite size need to be considered when calculating the pair distribution function (PDF). To achieve this, the simulation box must be set up to remove the periodic boundary condition in one, two or three of the dimensions. This then requires a correction to be applied for the difference in number density between the real system and the simulation box. In certain circumstances an analytical correction for the uncorrelated pairings of atoms is also applied. The validity and applicability of our methodology is demonstrated by applying the algorithms to simulate the PDF patterns of carbon systems with various dimensions, and also by using them to fit experimental data of CuO nanoparticles. This alternative approach for characterizing the local structure of nano-systems with the total scattering technique will be made available via the RMCProfile package. The theoretical formulation and detailed explanation of the analytical corrections for low-dimensional systems – 2D nanosheets, 1D nanowires and 0D nanoparticles – is also given.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Improved frame-based estimation of head motion in PET brain imaging

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is not susceptible to motion introduced between CT and PET acquisitions. Conclusions: The authors have shown that they can estimate motion for frames with time intervals as short as 5 s using nonattenuation corrected reconstructed FDG PET brain images. Intraframe motion in 60-s frames causes degradation of accuracy to about 2 mm based on the motion type.

60 APPLIED LIFE SCIENCES↗