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A novel optical architecture (based on holographic optical elements) for making high speed tomographic measurements is presented. The system is designed for making density or species concentration measurements in a nonsteady fluid or combusting flow. Performance evaluations of the optical system are discussed, and a test phase object has been successfully reconstructed using this optical arrangement.
A concept is presented for a high-resolution EUV/soft-X-ray imager that has much in common with the medical imaging procedure of tomography. The resulting instrument is compatible with a simpler, less costly spin-axis-stabilized spacecraft. To demonstrate the fidelity of the reconstruction procedure, the observation and reconstruction is simulated to compare the results with the original image.
Plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and interfacing material properties. For example, guided streamers that transition to surface ionization waves (SIWs) and propagate over structured dielectrics experience field enhancements that can lead to localized increases in ionization rates and complex 3D configurations that are difficult to analyze. Investigating these configurations requires techniques than can provide a more complete 3D picture. To help address this capability gap, a tomographic optical emission spectroscopy (tomo-OES) diagnostic system has been developed at Sandia National Laboratories that can resolve SIWs. The system includes four intensified cameras that measure the angular projections of the plasma light emission through bandpass filters. A dot calibration target co-registers each angular projection to the same voxel grid and an algebraic reconstruction technique (ART) recovers the light intensity at each voxel. An atmospheric pressure plasma jet (APPJ), provided by Peter Bruggeman, has been investigated and representative results are shown in Figure 1. Here, a bandpass filter was used to isolate emission from the N 2 second positive system (SPS) at 337.1 nm to capture the transition of the streamer to SIW on a planar dielectric surface (relative permittivity 3.3) located 3 mm below the APPJ [3]. The surface wave velocity was 3.5x10 4 (m/s), consistent with measurements made by Steven Shannon. Characterization of this APPJ will support the group effort of standing up a reproducible APPJ across institutions for applications such as liquid treatment, catalysis, and plasma aided combustion. Future work will investigate non-planar surfaces and eventually develop tomographic laser-induced fluorescence (tomo-LIF) approaches.
The purpose of this research is to examine the value of magnetic resonance imaging (MRI) as a means of conducting kinematic studies of the hand for the purpose of EVA capability enhancement. After imaging the subject hand using a magnetic resonance scanner, the resulting 2D slices were reconstructed into a 3D model of the proximal phalanx of the left hand. Using the coordinates of several landmark positions, one is then able to decompose the motion of the rigid body. MRI offers highly accurate measurements due to its tomographic nature without the problems associated with other imaging modalities for in vivo studies.
Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial for understanding how large-scale environment influences galaxy evolution. We combine wide-field Lyα imaging from the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey with extensive Dark Energy Spectroscopic Instrument and ancillary spectroscopy across the extended COSMOS and XMM Large Scale Structure (LSS) fields (≈14 deg$^{2}$) to search for massive protoclusters. We confirm six systems at z ≈ 2.4 and ≈ 3.1, including three newly identified structures and three which overlap with previously known structures and/or systems detected using other tracers. We reconstruct their three-dimensional structures, estimate descendant halo masses, and for one structure at z ≈ 3.12, demonstrate that overlapping narrowband filters (NB497 and N501) provide accurate redshift tomography for emission-line galaxies. One protocluster at z ≈ 2.45 overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H i overdensities traced by Lyα forest absorption. Another at z ≈ 3.12 hosts a massive quiescent galaxy (M$_{*}$ ≈ 1.2 × 10$^{11}$M$_{⊙}$), suggesting that overdense environments may play a role in accelerating galaxy assembly and quenching. Comparing Lyα emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when combining 2D and 3D density information, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at z ≈ 3.1 than at z ≈ 2.4, suggesting possible redshift evolution.
A new method of analyzing the kinematics of joint motion is developed. Magnetic Resonance Imaging (MRI) offers several distinct advantages. Past methods of studying anatomic joint motion have usually centered on four approaches. These methods are x-ray projection, goniometric linkage analysis, sonic digitization, and landmark measurement of photogrammetry. Of these four, only x-ray is applicable for in vivo studies. The remaining three methods utilize other types of projections of inter-joint measurements, which can cause various types of error. MRI offers accuracy in measurement due to its tomographic nature (as opposed to projection) without the problems associated with x-ray dosage. Once the data acquisition of MR images was complete, the images were processed using a 3D volume rendering workstation. The metacarpalphalangeal (MCP) joint of the left index finger was selected and reconstructed into a three-dimensional graphic display. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones were obtained and processed by analyzing the screw motion of the MCP joint. Landmark positions were chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily two dimensional planar motion of this joint was then studied using a method of constructing coordinate systems using three (or more) points. A transformation matrix based on a world coordinate system described the location and orientation of a local target coordinate system. Future research involving volume rendering of MRI data focusing on the internal kinematics of the hand's individual ligaments, cartilage, tendons, etc. will follow. Its findings will show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove (power assisted) design for extravehicular activity (EVA).
This work presents an application of Model Predictive Control to maintain long-term stability for a three-satellite formation around the asteroid Apophis via remote guidance. The mothership and two daughterships perform tomographic characterization with a bistatic radar. The mothership estimates the states of all three spacecraft and determines the necessary control to maintain the desired antipodal daughtership states. An Extended Kalman Filter estimates the mothership states. A Batch Least Squares algorithm estimates the daughtership states and performs maneuver reconstruction for the mothership-administered thrust commands under thruster and gravitational uncertainty. The formulation maintains the antipodal angle with growing instability amidst these uncertainties.
A nuclear imaging system and method for performing three-dimensional imaging of anatomical structures. The system and method includes two or more gamma ray detectors each used in combination with a variable-slant hole collimator. The detectors are positioned in close proximity to, or in contact with, the structure being imaged. The detectors remain in a stationary position during the data collection process. An imaging or reconstruction method is then used to reconstruct a three-dimensional image from the data derived from the detectors.
A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: X.sup.(k+1).spsp.T =?Y.sup.T W+X.sup.(k).spsp.T .LAMBDA.!?W.sup.T W+.LAMBDA.!.sup.-1 wherein W is a matrix relating output at detector position r.sub.d, at time t, to source at position r.sub.s, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Here Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information.
A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absorption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.
A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.
Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.
An image reconstruction technique was developed to overcome problems with earlier methods of gamma emission computed tomography of graphite rings surrounding the AGR-3/4 TRISO fission product transport experiment. The profiles obtained from the tomography are compared with sampling done via radially resolved destructive sampling techniques. Generally, there is good agreement between profiles measured via destructive sampling of the rings and the tomographic profiles, though at low signal strengths, the tomographic profiles appear elevated.
X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.
Abstract Owing in large part to the advent of integrated biphoton frequency combs, recent years have witnessed increased attention to quantum information processing in the frequency domain for its inherent high dimensionality and entanglement compatible with fiber-optic networks. Quantum state tomography of such states, however, has required complex and precise engineering of active frequency mixing operations, which are difficult to scale. To address these limitations, we propose a solution that employs a pulse shaper and electro-optic phase modulator to perform random operations instead of mixing in a prescribed manner. We successfully verify the entanglement and reconstruct the full density matrix of biphoton frequency combs generated from an on-chip Si 3 N 4 microring resonator in up to an 8 × 8-dimensional two-qudit Hilbert space, the highest dimension to date for frequency bins. More generally, our employed Bayesian statistical model can be tailored to a variety of quantum systems with restricted measurement capabilities, forming an opportunistic tomographic framework that utilizes all available data in an optimal way.
Background: The quality of Digital Volume Correlation (DVC) full-field displacement measurements depends directly on the characteristics of the X-ray Computed Tomography (XCT) equipment, and scan procedures used to acquire the tomographic images. Objective: In this work, we seek to experimentally study the effects of XCT equipment and tomographic scan procedures on the quality of these images for DVC analysis, and to survey the level of DVC error that may be achieved using standard XCT operating procedures. Methods: Six participants in an interlaboratory study acquired high-quality XCT scans of a syntactic foam before and after rigid body motion. The resulting images were correlated using commercial DVC software to quantify error sources due to random image noise, reconstruction artifacts, as well as systematic spatial or temporal distortion. Results: In the absence of rigid body motion, the standard deviation of the displacement measurements ranged from 0.012 to 0.043 voxels using a moderate subvolume size, indicating that subvoxel measurement resolution could readily be achieved with a variety of XCT equipment and scan recipes. Comparison of consecutive scans without rigid body motion showed transient dilatational displacement gradients due to self-heating of the X-ray source and/or thermal expansion of the foam. Evaluation of the scans after rigid body motion showed significant, machine-specific spatial distortion in the displacement fields of up to 0.5 voxels; new approaches to remove this error need to be developed. Conclusions: Analysis of the scan protocols used in the interlaboratory study, as well as a complementary parametric sensitivity study, showed that the DVC error was strongly influenced by the XCT equipment, but could be mitigated by adjusting the total scan duration.
Tomographic microwave diversity imaging is analyzed using linear system theory concepts, and optimal spectral windows for data acquisition are obtained either by considering window position in the spectral domain or by using simulated annealing to find an optimal phase weighting of the object frequency response samples collected over the specified spectral window. This study provides a means of microwave image formation that is applicable under general assumptions. Results of numerical simulations and representative images reconstructed from realistic experimental microwave scattering data are given, demonstrating that the proposed approach is superior to previous image reconstruction methods.
Three-dimensional inspection of nanostructures such as integrated circuits is important for security and reliability assurance. Two scanning operations are required: ptychographic to recover the complex transmissivity of the specimen, and rotation of the specimen to acquire multiple projections covering the 3D spatial frequency domain. Two types of rotational scanning are possible: tomographic and laminographic. For flat, extended samples, for which the full 180° coverage is not possible, the latter is preferable because it provides better coverage of the 3D spatial frequency domain compared to limited-angle tomography. It is also because the amount of attenuation through the sample is approximately the same for all projections. However, both techniques are time consuming because of extensive acquisition and computation time. Here, we demonstrate the acceleration of ptycho-laminographic reconstruction of integrated circuits with 16 times fewer angular samples and 4.67 times faster computation by using a physics-regularized deep self-supervised learning architecture. We check the fidelity of our reconstruction against a densely sampled reconstruction that uses full scanning and no learning. As already reported elsewhere [ Opt. Express 28 , 12872 ( 2020 ) OPEXFF 1094-4087 10.1364/OE.379200 ], we observe improvement of reconstruction quality even over the densely sampled reconstruction, due to the ability of the self-supervised learning kernel to fill the missing cone.