Uniform Attenuation Research Articles

Attention modulates early visual processing: An association between subjective contrast perception and early C1 ERP component.

The question of whether spatial attention can modulate initial afferent activity in area V1, as measured by the earliest visual event-related potential (ERP) component "C1", is still the subject of debate. Because attention always enhances behavioral performance, previous research has focused on finding evidence of attention-related enhancements in visual neural responses. However, recent psychophysical studies revealed a complex picture of attention's influence on visual perception: attention amplifies the perceived contrast of low-contrast stimuli while dampening the perceived contrast of high-contrast stimuli. This evidence suggests that attention may not invariably augment visual neural responses but could instead exert inhibitory effects under certain circumstances. Whether this bi-directional modulation of attention also manifests in C1 and whether the modulation of C1 underpins the attentional influence on contrast perception remain unknown. To address these questions, we conducted two experiments (N = 67 in total) by employing a combination of behavioral and ERP methodologies. Our results did not unveil a uniform attentional enhancement or attenuation effect of C1 across all subjects. However, an intriguing correlation between the attentional effects of C1 and contrast appearance for high-contrast stimuli did emerge, revealing an association between attentional modulation of C1 and the attentional modulation of contrast appearance. This finding offers new insights into the relationship between attention, perceptual experience, and early visual neural processing, suggesting that the attentional effect on subjective visual perception could be mediated by the attentional modulation of the earliest visual cortical response.

Generative adversarial network-based attenuation correction for 99mTc-TRODAT-1 brain SPECT.

Attenuation correction (AC) is an important correction method to improve the quantification accuracy of dopamine transporter (DAT) single photon emission computed tomography (SPECT). Chang's method was developed for AC (Chang-AC) when CT-based AC was not available, assuming uniform attenuation coefficients inside the body contour. This study aims to evaluate Chang-AC and different deep learning (DL)-based AC approaches on 99mTc-TRODAT-1 brain SPECT using clinical patient data on two different scanners. Two hundred and sixty patients who underwent 99mTc-TRODAT-1 SPECT/CT scans from two different scanners (scanner A and scanner B) were retrospectively recruited. The ordered-subset expectation-maximization (OS-EM) method reconstructed 120 projections with dual-energy scatter correction, with or without CT-AC. We implemented a 3D conditional generative adversarial network (cGAN) for the indirect deep learning-based attenuation correction (DL-ACμ) and direct deep learning-based attenuation correction (DL-AC) methods, estimating attenuation maps (μ-maps) and attenuation-corrected SPECT images from non-attenuation-corrected (NAC) SPECT, respectively. We further applied cross-scanner training (cross-scanner indirect deep learning-based attenuation correction [cull-ACμ] and cross-scanner direct deep learning-based attenuation correction [call-AC]) and merged the datasets from two scanners for ensemble training (ensemble indirect deep learning-based attenuation correction [eDL-ACμ] and ensemble direct deep learning-based attenuation correction [eDL-AC]). The estimated μ-maps from (c/e)DL-ACμ were then used in reconstruction for AC purposes. Chang's method was also implemented for comparison. Normalized mean square error (NMSE), structural similarity index (SSIM), specific uptake ratio (SUR), and asymmetry index (%ASI) of the striatum were calculated for different AC methods. The NMSE for Chang's method, DL-ACμ, DL-AC, cDL-ACμ, cDL-AC, eDL-ACμ, and eDL-AC is 0.0406 ± 0.0445, 0.0059 ± 0.0035, 0.0099 ± 0.0066, 0.0253 ± 0.0102, 0.0369 ± 0.0124, 0.0098 ± 0.0035, and 0.0162 ± 0.0118 for scanner A and 0.0579 ± 0.0146, 0.0055 ± 0.0034, 0.0063 ± 0.0028, 0.0235 ± 0.0085, 0.0349 ± 0.0086, 0.0115 ± 0.0062, and 0.0117 ± 0.0038 for scanner B, respectively. The SUR and %ASI results for DL-ACμ are closer to CT-AC, Followed by DL-AC, eDL-ACμ, cDL-ACμ, cDL-AC, eDL-AC, Chang's method, and NAC. All DL-based AC methods are superior to Chang-AC. DL-ACμ is superior to DL-AC. Scanner-specific training is superior to cross-scanner and ensemble training. DL-based AC methods are feasible and robust for 99mTc-TRODAT-1 brain SPECT.

Bolus 3D printing for radiotherapy with conventional PLA, ABS and TPU filaments: Theoretical-experimental study

A theoretical-experimental study of the interaction of electron beams with 3 filaments conventionally used for 3D printing is presented in this paper. Pieces of polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) and thermoplastic polyurethane (TPU) are studied using Monte Carlo simulation with Geant4 and experimental measurements with plane-parallel ionization chambers and radiochromic films. Using different printing parameters and computed tomography, the presence of air gaps and the uniformity in the bolus density made with the different materials are evaluated. The main parameters in the Percentage Depth Dose (PDDs) are determined, the manufacturing process is standardized and the printing profiles are generated for each of the materials in order to obtain uniform attenuation characteristics in the pieces and improve adaptation to irregular anatomical areas.

No impact of attenuation and scatter correction on the interpretation of dopamine transporter SPECT in patients with clinically uncertain parkinsonian syndrome

PurposeThe benefit from attenuation and scatter correction (ASC) of dopamine transporter (DAT)-SPECT for the detection of nigrostriatal degeneration in clinical routine is still a matter of debate. The current study evaluated the impact of ASC on visual interpretation and semi-quantitative analysis of DAT-SPECT in a large patient sample.MethodsOne thousand seven hundred forty consecutive DAT-SPECT with 123I-FP-CIT from clinical routine were included retrospectively. SPECT images were reconstructed iteratively without and with ASC. Attenuation correction was based on uniform attenuation maps, scatter correction on simulation. All SPECT images were categorized with respect to the presence versus the absence of Parkinson-typical reduction of striatal 123I-FP-CIT uptake by three independent readers. Image reading was performed twice to assess intra-reader variability. The specific 123I-FP-CIT binding ratio (SBR) was used for automatic categorization, separately with and without ASC.ResultsThe mean proportion of cases with discrepant categorization by the same reader between the two reading sessions was practically the same without and with ASC, about 2.2%. The proportion of DAT-SPECT with discrepant categorization without versus with ASC by the same reader was 1.66% ± 0.50% (1.09–1.95%), not exceeding the benchmark of 2.2% from intra-reader variability. This also applied to automatic categorization of the DAT-SPECT images based on the putamen SBR (1.78% discrepant cases between without versus with ASC).ConclusionGiven the large sample size, the current findings provide strong evidence against a relevant impact of ASC with uniform attenuation and simulation-based scatter correction on the clinical utility of DAT-SPECT to detect nigrostriatal degeneration in patients with clinically uncertain parkinsonian syndrome.

A First Look at Spatially Resolved Balmer Decrements at 1.0 < z < 2.4 from JWST NIRISS Slitless Spectroscopy

We present the first results on the spatial distribution of dust attenuation at 1.0 < z < 2.4 traced by the Balmer decrement, Hα/Hβ, in emission-line galaxies using deep JWST NIRISS slitless spectroscopy from the CAnadian NIRISS Unbiased Cluster Survey (CANUCS). Hα and Hβ emission-line maps of emission-line galaxies are extracted and stacked in bins of stellar mass for two grism redshift bins, 1.0 < z grism < 1.7 and 1.7 < z grism < 2.4. Surface brightness profiles for the Balmer decrement are measured and radial profiles of the dust attenuation toward Hα, A Hα , are derived. In both redshift bins, the integrated Balmer decrement increases with stellar mass. Lower-mass (7.6 ≤ Log(M */M ⊙) < 10.0) galaxies have centrally concentrated, negative dust attenuation profiles whereas higher-mass galaxies (10.0 ≤ Log(M */M ⊙) < 11.1) have flat dust attenuation profiles. The total dust obscuration is mild, with on average 0.07 ± 0.07 and 0.14 ± 0.07 mag in the low- and high-redshift bins respectively. We model the typical light profiles of star-forming galaxies at these redshifts and stellar masses with GALFIT and apply both uniform and radially varying dust attenuation corrections based on our integrated Balmer decrements and radial dust attenuation profiles. If the Hα star formation rates (SFRs) of these galaxies were measured after slit-loss corrections assuming uniform dust attenuation with typical JWST NIRSpec slit spectroscopy (0.″2 × 0.″5 shutters), the total SFR will be overestimated by 6% ± 21% and 26% ± 9% at 1.0 ≤ z < 1.7 and 1.7 ≤ z < 2.4 respectively.

Preliminary Investigation of Perceived Sound Quality for High-Fidelity Premolded Hearing Protection Devices

High-fidelity premolded earplugs (HiFi HPDs) are designed to provide relatively uniform attenuation across frequencies. The primary goal of this study was an exploratory analysis of relationships between attenuation and perceptions of sound quality. Participants were 16 adults tested using commercial HiFi HPDs marketed for use at recreational music events. Survey responses did not reveal statistically significant differences in perceived sound quality across HiFi HPD brands. However, increases in music quality ratings were correlated with decreases in average attenuation at 3, 4, and 6 kHz and increasing uniformity of attenuation. The correlations were weak, however, explaining only about 15% of the variance. The data suggest listeners may prefer HiFi HPDs that provide more uniform sound attenuation at frequencies from 0.25 to 4 kHz and less attenuation from 3 to 6 kHz. The data are consistent with existing suggestions that HiFi HPDs with moderate but uniform attenuation may be preferred by those listening to music.

Optimizing the performance of a side-branch array duct muffler

Recent studies of the authors show that muffler formed by putting together narrow side-branches in array form can offer strong and broadband sound attenuation in low Mach number flow ducts. It is also found that such muffler with the increasing branch length in the direction of duct flow has stronger resilience to flow excitation and thus can maintain its sound attenuation performance unless the duct flow is high. However, the arrangement of the branch length has not been optimized. Numerical investigation is carried out using finite-element computation in the present study to further understand how the branch length variation is affecting the overall sound attenuation of the side-branch array muffler. For simplicity, a branch length variation is assumed to follow a power law of the branch order. A power law index of 1 represents linear variation. It is found that for a muffler with 11 side-branches, the index for minimum transmission is about 1.5, but that for maximum particle kinetic energy is around 1.38. In term of noise attenuation spectrum, the muffler with index 1 and 3 give very strong attenuation at particular frequencies, while that with index 1.5 gives a more uniform attenuation within the operation frequency range.

Deterministic Modeling for Radiation Attenuation-integrated Radon Transform in Emission Computed Tomography: Algorithm, Curve Fitting Analysis, and Introduction of Attenuation Hadamard Matrix.

The purpose of the study is to propose an algorithm to implement and visualize radiation attenuation-integrated Radon transform based on Beer-Lambert law during emission computed tomography simulation using a deterministic model and also to perform image analysis on resulting images. Two types of phantoms are designed: plain-disk phantom and patterned-disk phantom. The large disk is filled with an activity of 5 units and the smaller disks have 10 units of activity of 99mTc isotope as an emission map. Three transmission maps for patterned-disk phantom are created with uniform linear attenuation coefficient. Phantoms are scanned with 360° and 180° acquisition arcs. Then, using the algorithm designed, the exponential Radon transform is implemented. After that, the projections are back-projected and filtered to generate tomographic slices. Finally, all slices are analyzed using profile plotting and curve fitting. Moreover, an attenuation Hadamard matrix is provided to facilitate attenuation modeling. The uniform intensity of activity in the phantoms is converted to a disk with progressively decreasing intensity from the periphery to the center in the tomographic slices. Similarly, the circles positioned more centrally appear less intense than those positioned in the periphery, despite all circles having equal activity. When the phantom is scanned in 180° arc, the circles closest to the camera are visualized more intensely. The profile curves of the slices generated by exponential Radon transformation are depicted as U-shaped in profile plotting and are fitted to a bi-exponential function with a near-perfect precision. The incorporation of radiation attenuation results in the development of more realistic models for quantification purposes.

EarBloom: A Bio-Inspired Intersection of High-Fidelity Hearing Protection and Fashion Technology

Noise pollution has become an increasingly prevalent issue due to audio digitization in the modern world and can cause permanent damage to the ear. However, currently available hearing protection devices distort sound attenuation and are unpopular because they lack comfort and aesthetic appeal. Soft robotics enable new possibilities for morphological hearing protection that, when integrated with fashion, offer a modern and artistic solution. In this paper, we present EarBloom as a solution to combat hearing damage. Inspired by the natural blooming of a flower, EarBloom's folding actuation and high-fidelity chambers were designed and tested in 3D modeling software and utilize electrical stimuli to protect the ear automatically. EarBloom is an innovative, soft-robotic approach to hearing protection that integrates automatic protection, uniform attenuation, and aesthetic appeal.

Verification of Attenuation for Premolded Hearing Protection Devices Designed for Music.

High-fidelity premolded earplugs (HiFi HPDs) are designed to provide relatively uniform attenuation across frequencies. The primary goal of this study was to verify the amount and flatness of individual user attenuation. HiFi HPD attenuation was measured using real-ear attenuation at threshold (REAT) measurements under circumaural earphones. Participants were 16 adults tested using commercial HiFi HPDs marketed for use at recreational music events and/or for use by musicians. There was significant individual variation in attenuation both within and across HiFi HPD brands. In addition to significant differences in achieved attenuation, there were significant differences in the uniformity of the attenuation. These data suggest verification of attenuation is important in musicians who are at risk for music-induced hearing disorders even when using "over-the-counter" uniform-fit HPDs.

Deep learning-guided attenuation correction in the image domain for myocardial perfusion SPECT imaging

Abstract We investigate the accuracy of direct attenuation correction (AC) in the image domain for myocardial perfusion SPECT (single-photon emission computed tomography) imaging (MPI-SPECT) using residual (ResNet) and UNet deep convolutional neural networks. MPI-SPECT 99mTc-sestamibi images of 99 patients were retrospectively included. UNet and ResNet networks were trained using non-attenuation-corrected SPECT images as input, whereas CT-based attenuation-corrected (CT-AC) SPECT images served as reference. Chang’s calculated AC approach considering a uniform attenuation coefficient within the body contour was also implemented. Clinical and quantitative evaluations of the proposed methods were performed considering SPECT CT-AC images of 19 subjects (external validation set) as reference. Image-derived metrics, including the voxel-wise mean error (ME), mean absolute error, relative error, structural similarity index (SSI), and peak signal-to-noise ratio, as well as clinical relevant indices, such as total perfusion deficit (TPD), were utilized. Overall, AC SPECT images generated using the deep learning networks exhibited good agreement with SPECT CT-AC images, substantially outperforming Chang’s method. The ResNet and UNet models resulted in an ME of −6.99 ± 16.72 and −4.41 ± 11.8 and an SSI of 0.99 ± 0.04 and 0.98 ± 0.05, respectively. Chang’s approach led to ME and SSI of 25.52 ± 33.98 and 0.93 ± 0.09, respectively. Similarly, the clinical evaluation revealed a mean TPD of 12.78 ± 9.22% and 12.57 ± 8.93% for ResNet and UNet models, respectively, compared to 12.84 ± 8.63% obtained from SPECT CT-AC images. Conversely, Chang’s approach led to a mean TPD of 16.68 ± 11.24%. The deep learning AC methods have the potential to achieve reliable AC in MPI-SPECT imaging.

High-Selectivity Bandpass Filter with Controllable Attenuation Based on Graphene Nanoplates.

A high-selectivity band pass filter with controllable attenuation based on graphene nanoplates is proposed in this paper. Graphene with controllable resistance has a good uniform attenuation effect to electric field intensity. The filter utilizes quarter wavelength stepped impedance resonators and mixed electromagnetic coupling to have compact circuits and high performance. The graphene nanoplates are loaded on the microstrip resonator to reduce the electric field intensity, which results in a flat attenuation in the passband. In addition, the filter has two transmission zeros, which lead to a strong selectivity. Finally, a high-selectivity bandpass filter with controllable attenuation is formed. By changing the bias voltage of graphene, a controllable attenuation of 1.64–11.13 dB can be achieved in the working passband centered at 1.36 GHz. In order to validate the concept, the prototype is fabricated and measured. The measurement results are in good agreement with the simulation results. The proposed high-selectivity bandpass filter with controllable attenuation based on graphene nanoplates has widely potential in reconfigurable wireless communication systems and radar systems due to its high integration and versatility.

Evaluation of hearing protection device effectiveness for musicians

Objective To evaluate musicians’ personal attenuation and perceptions of three types of hearing protection devices (HPDs): formable foam earplugs and both non-custom and custom versions of uniform attenuation earplugs (UAEs) marketed to musicians. Design A mixed-methods approach was used to evaluate the HPDs. Audiometric testing obtained hearing levels at baseline and with each HPD across frequencies (125–8000 Hz) to determine personal attenuation ratings and uniformity of attenuation. Participants completed surveys over six months regarding how often they used the HPDs and their perceptions about wearing them. Study sample Twenty-four musicians were recruited to participate. Results Substantial variability was observed in the attenuation achieved among participants for each HPD type, but custom UAEs provided the most consistent attenuation across frequencies. Participants’ HPD preferences were influenced by multiple factors including personal instrument and specific activity. Custom UAEs were most frequently used but usage rates continually decreased over the 6-month period. Conclusions Fit-testing is important to determine fit and sizing. Combining information on the effectiveness of HPDs with musicians’ opinions about wearing them can inform recommendations for which types may be the most effective and feasible options for reducing sound exposures.

Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

A tomographic patient model is essential for radiation dose modulation in x-ray computed tomography (CT). Currently, two-view scout images (also known as topograms) are used to estimate patient models with relatively uniform attenuation coefficients. These patient models do not account for the detailed anatomical variations of human subjects, and thus, may limit the accuracy of intraview or organ-specific dose modulations in emerging CT technologies. The purpose of this work was to show that 3D tomographic patient models can be generated from two-view scout images using deep learning strategies, and the reconstructed 3D patient models indeed enable accurate prescriptions of fluence-field modulated or organ-specific dose delivery in the subsequent CTscans. CT images and the corresponding two-view scout images were retrospectively collected from 4214 individual CT exams. The collected data were curated for the training of a deep neural network architecture termed ScoutCT-NET to generate 3D tomographic attenuation models from two-view scout images. The trained network was validated using a cohort of 55136 images from 212 individual patients. To evaluate the accuracy of the reconstructed 3D patient models, radiation delivery plans were generated using ScoutCT-NET 3D patient models and compared with plans prescribed based on true CT images (gold standard) for both fluence-field-modulated CT and organ-specific CT. Radiation dose distributions were estimated using Monte Carlo simulations and were quantitatively evaluated using the Gamma analysis method. Modulated dose profiles were compared against state-of-the-art tube current modulation schemes. Impacts of ScoutCT-NET patient model-based dose modulation schemes on universal-purpose CT acquisitions and organ-specific acquisitions were also compared in terms of overall image appearance, noise magnitude, and noiseuniformity. The results demonstrate that (1) The end-to-end trained ScoutCT-NET can be used to generate 3D patient attenuation models and demonstrate empirical generalizability. (2) The 3D patient models can be used to accurately estimate the spatial distribution of radiation dose delivered by standard helical CTs prior to the actual CT acquisition; compared to the gold-standard dose distribution, 95.0% of the voxels in the ScoutCT-NET based dose maps have acceptable gamma values for 5 mm distance-to-agreement and 10% dose difference. (3) The 3D patient models also enabled accurate prescription of fluence-field modulated CT to generate a more uniform noise distribution across the patient body compared to tube current-modulated CT. (4) ScoutCT-NET 3D patient models enabled accurate prescription of organ-specific CT to boost image quality for a given body region-of-interest under a given radiation doseconstraint. 3D tomographic attenuation models generated by ScoutCT-NET from two-view scout images can be used to prescribe fluence-field-modulated or organ-specific CT scans with high accuracy for the overall objective of radiation dose reduction or image quality improvement for a given imagingtask.

Achievement and Philosophy of Studies on SPECT Reconstruction Algorithms

The purpose of this article is to introduce achievement and philosophy on studies of SPECT reconstruction algorithms which Dr. Eiichi Tanaka dedicated himself to carrying out. The method that Dr. Tanaka suggested first (in 1974) was to reconstruct analytically a section image from the projection data convoluted the correction functions. The correction functions were optimized to yield a maximum 'signal-to-noise ratio'. In 1983 and 1984, two image reconstruction algorithms, WBP and RPC were suggested assuming a uniform attenuation in the object. Dr. Tanaka understood intuitively that these methods had few noise and distortions in reconstructed images. WBP was an approximate solution, but three type analytically methods were reported by Tretiak O, et al., Bellini S, et al., and Inoyue T, et al. In 1995, Metz CE, et al. and Kudo H, et al. succeeded independently each other in finishing a general theory of the analytic absorption Radon Conversion by using parameter "n". The relations among the above three analytically methods and WBP were explained, beautifully. The important thing in the study is a flexible idea such as catching a problem as the issue of black box or reverse and the result to be concise and elegant.

Plaque Characterization with Computed Tomography Angiography Based on a Diluted-contrast Injection Protocol.

Objective Coronary plaques with low attenuation on computed tomography (CT) angiography may indicate vulnerable plaques. However, plaque CT attenuation is reported to be significantly affected by intracoronary attenuation. Recently, the diluted-contrast injection protocol was established to facilitate more uniform intracoronary attenuation than can be achieved with the generally used body-weight-adjusted protocol. We validated the relationship between low-attenuation plaque on CT and lipid-rich plaque using integrated backscatter-intravascular ultrasound (IB-IVUS) as the standard reference. Methods Plaques were divided into tertiles (T1, T2, and T3) according to the plaque CT attenuation, calculated as the average of five intra-plaque regions of interest, and compared with the plaque characteristics noted on IB-IVUS. Patients Patients who underwent both CT angiography using a diluted-contrast injection protocol and IB-IVUS were retrospectively analyzed. Results Thirty-nine plaques in 32 patients were analyzed by CT angiography and IB-IVUS. The median plaque CT attenuation (Hounsfield units) of each tertile was 30 (T1), 48 (T2), and 68 (T3). Although no significant difference was noted in conventional quantitative IVUS parameters (e.g. plaque burden), the T1 with lowest plaque CT attenuation had the highest percentage lipid area by IB-IVUS [75.1% (T1), 57.8% (T2), and 50.8% (T3), respectively, p<0.01]. Furthermore, the plaque CT attenuation had a significant negative correlation with the percentage lipid area (r=-0.59, p<0.01). Conclusion CT angiography-based plaque characterization using a diluted-contrast injection protocol may aid in the quantitative detection of lipid-rich plaque.

Statistics of Complex Wigner Time Delays as a Counter of S-Matrix Poles: Theory and Experiment.

We study the statistical properties of the complex generalization of Wigner time delay τ_{W} for subunitary wave-chaotic scattering systems. We first demonstrate theoretically that the mean value of the Re[τ_{W}] distribution function for a system with uniform absorption strength η is equal to the fraction of scattering matrix poles with imaginary parts exceeding η. The theory is tested experimentally with an ensemble of microwave graphs with either one or two scattering channels and showing broken time-reversal invariance and variable uniform attenuation. The experimental results are in excellent agreement with the developed theory. The tails of the distributions of both real and imaginary time delay are measured and are also found to agree with theory. The results are applicable to any practical realization of a wave-chaotic scattering system in the short-wavelength limit, including quantum wires and dots, acoustic and electromagnetic resonators, and quantum graphs.

Design and Characterization of a Neutron-Friendly Lithium-Ion Battery Coin Cell for Extreme Fast-Charging

Lithium-ion batteries (LIBs) have profoundly advanced the development of electric vehicles (EV). However, one of the remaining bottlenecks in their widespread deployment is the long charging time typically required for commercial LIBs. There is a global push towards extreme fast charging (XFC) of EV batteries to reduce their charging times to 10-15 minutes.1 However, XFC causes severe degradation in the electrochemical performance of LIBs, which is mainly attributed to irreversible Li plating on the surface of the graphite anode rather than intercalation of Li ions inside the graphite as the battery is fast-charged.2 Since Li plating has been identified as one of the major XFC degradation mechanisms Bs, understanding its origin and spatial heterogeneity across three dimensions (3D) on porous graphite anodes as a function of time necessitates a non-destructive characterization platform to differentiate between graphite and Li.Neutron-based imaging provides the sensitivity to differentiate graphite from Li due to the large difference in their total neutron cross-sections (Li:C ~ 73:11 barns). However, high energy X-rays enable penetrating the metallic battery components. e.g., Cu, Al. We tested the feasibility of simultaneous neutron and X-ray tomography (NeXT) on the BT-2 imaging beamline at National Institute of Standards and Technology Center for Neutron Research.4 Our spatial resolution for both X-rays and neutrons was ~15-20 μm. For ex-situ Li plating detection, we imaged 1) pristine, and 2) a cycled graphite anode.5 For cycled anode, we disassembled the battery pouch cells in their fully discharged condition and harvested the anode after 450 cycles of 9C charging and C/2 discharging. For data analysis, we used 2D bivariate histogram phase segmentation to differentiate different battery materials such as Cu, graphite, etc. However, low X-ray energy (40keV) combined with the flat sample geometry of the graphite strips made it challenging to remove beam hardening artifacts from copper and, therefore, to segment lithium from graphite. In addition, to determine NeXT feasibility for in-situ imaging, we also characterized a fully assembled, uncycled single-layer battery pouch cell. However, the high neutron attenuation by the hydrogen in EC: EMC (3:7) electrolyte and hydrogenous polymeric materials in the Celgard separator made it particularly difficult to segment graphite anode from the separator and positively identify interfaces.In this presentation, we will outline the design and characterization of a neutron-friendly LIB coin cell for extreme fast-charging. Our design is based on a standard 2032 format coin cell with custom modifications to address the dual criteria of electrochemistry and neutron imaging, i.e., good neutron transmission and relative contrast from a functional LIB at 6-C charging rate. We will present three advantages of coin cell geometry: 1) it provides more uniform attenuation throughout the entire tomography scan thus, reducing artifacts; 2) multiple coin cells can be stacked on top of each other for high throughput battery imaging; 3) it reduces the amount of expensive deuterated materials needed while developing the optimum cell configurations. In addition, we will address the need of a deuterated EC: DMC electrolyte in a fluorinated separator for the neutron-friendly battery design (Figure 1). Since the total neutron cross-section of deuterium and fluorine are on the orders of magnitude lower than that of hydrogen, we anticipate that these modifications will increase neutron transmission through the battery, thus improving signal-to-noise ratio and reducing acquisition time especially at low neutron flux facilities. Secondly, they will result in a cleaner electrolyte-separator-anode interface for the detection of plated lithium because of absence of hydrogen. Finally, we will show how these modifications affect the electrochemical performance of our LIB coin cells to determine the onset of Li plating at 6-C charging rate. i-e., capacity fade vs. number of cycles.

Attenuation correction using deep learning for brain perfusion SPECT images.

Non-uniform attenuation correction using computed tomography (CT) improves the image quality and quantification of single-photon emission computed tomography (SPECT). However, it is not widely used because it requires a SPECT/CT scanner. This study constructs a convolutional neural network (CNN) to generate attenuation-corrected SPECT images directly from non-attenuation-corrected SPECT images. We constructed an auto-encoder (AE) using a CNN to correct the attenuation in brain perfusion SPECT images. SPECT image datasets of 270 (44,528 slices including augmentation), 60 (5002 slices), and 30 (2558 slices) cases were used for training, validation, and testing, respectively. The acquired projection data were reconstructed in three patterns: uniform attenuation correction using Chang's method (Chang-AC), non-uniform attenuation correction using CT (CT-AC), and no attenuation correction (No-AC). The AE learned an end-to-end mapping between the No-AC and CT-AC images. The No-AC images in the test dataset were loaded into the trained AE, which generated images simulating the CT-AC images as output. The generated SPECT images were employed as attenuation-corrected images using the AE (AE-AC). The accuracy of the AE-AC images was evaluated in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity metric (SSIM). The intensities of the AE-AC and CT-AC images were compared by voxel-by-voxel and region-by-region analysis. The PSNRs of the AE-AC and Chang-AC images, compared using CT-AC images, were 62.2, and 57.9, and their SSIM values were 0.9995 and 0.9985, respectively. The AE-AC and CT-AC images were visually and statistically in good agreement. The proposed AE-AC method yields highly accurate attenuation-corrected brain perfusion SPECT images.

A GIT algorithm for simultaneous estimation of seismic source, site response and regional-distance dependent attenuation parameters: application to synthetic and real data

The generalized inversion technique (GIT) of earthquake recordings is a useful tool in retrieving seismic source spectra, attenuation path parameters and site transfer functions (TF). Further understanding of these three fundamental factors which control seismic ground motion constitutes one of the main challenges in seismology. Especially, the site TF estimation is an important objective that can significantly contribute to seismic hazard assessment. In this study, a parametric GIT algorithm (in MATLAB (The MathWorks, Inc., Natick, Massachusetts, United States, 2017)), based on the one proposed by Drouet et al. (Bull Seism Soc Am 98:198–219, 2008a), is developed, by introducing distance- and regional-dependent attenuation parameters for geometrical spreading and anelastic attenuation terms, respectively. This step is aimed at a more detailed investigation of attenuation path, anticipating to improve the knowledge of all three fundamental factors controlling seismic ground motion. The algorithm is based on a Gauss-Newton iterative inversion method, using initial reasonable model parameters. Source term is parametrically investigated for seismic moment and corner frequency, which can be simultaneously controlled with respect to stress drop. A synthetic dataset, approximating a simplified real dataset was inverted by the proposed inversion algorithm examining its computational validity. Four tests were implemented, with or without reference condition, providing encouraging results. The applicability of the algorithm is supported by the inversion of a real dataset which was also examined by Grendas et al. (Bull Earthq Eng 16:5061–5094, 2018) using a uniform attenuation model in GIT. Approximately 9% reduction of the misfit between real and computed data from the inverted model data is achieved, showing the effectiveness of the proposed algorithm.