Ultrafast power Doppler imaging (uPDI) using high-frame-rate plane-wave transmission is a new microvascular imaging modality that offers high Doppler sensitivity. However, due to the unfocused transmission of plane waves, the echo signal is subject to interference from noise and clutter, resulting in a low signal-to-noise ratio (SNR) and poor image quality. Adaptive beamforming techniques are effective in suppressing noise and clutter for improved image quality. In this study, an adaptive beamformer based on a united spatial–angular adaptive scaling Wiener (uSA-ASW) postfilter is proposed to improve the resolution and contrast of uPDI. In the proposed method, the signal power and noise power of the Wiener postfilter are estimated by uniting spatial and angular signals, and a united generalized coherence factor (uGCF) is introduced to dynamically adjust the noise power estimation and enhance the robustness of the method. Simulation and in vivo data were used to verify the effectiveness of the proposed method. The results show that the uSA-ASW can achieve higher resolution and significant improvements in image contrast and background noise suppression compared with conventional delay-and-sum (DAS), coherence factor (CF), spatial–angular CF (SACF), and adaptive scaling Wiener (ASW) postfilter methods. In the simulations, uSA-ASW improves contrast-to-noise ratio (CNR) by 34.7 dB (117.3%) compared with DAS, while reducing background noise power (BNP) by 52 dB (221.4%). The uSA-ASW method provides full-width at half-maximum (FWHM) reductions of $301~\mu \text{m}$ (59.5%) and $568~\mu \text{m}$ (56.9%), CNR improvements of 25.6 dB (199.9%) and 42 dB (253%), and BNP reductions of 46.1 dB (319.3%) and 12.9 dB (289.1%) over DAS in the experiments of contrast-free human neonatal brain and contrast-free human liver, respectively. In the contrast-free experiments, uSA-ASW effectively balances the performance of noise and clutter suppression and enhanced microvascular visualization. Overall, the proposed method has the potential to become a reliable microvascular imaging technique for aiding in more accurate diagnosis and detection of vascular-related diseases in clinical contexts.
Ultrafast power Doppler imaging (uPDI) using high-frame-rate plane-wave transmission is a new microvascular imaging modality that offers high Doppler sensitivity. However, due to the unfocused transmission of plane waves, the echo signal is subject to interference from noise and clutter, resulting in a low signal-to-noise ratio and poor image quality. This study proposed an adaptive beamformer based on a united spatial-angular adaptive scaling Wiener postfilter to obtain high-quality microvessel images. The signal power and noise power of the Wiener postfilter are estimated by uniting spatial and angular signals, and a united generalized coherence factor is introduced to dynamically adjust the noise power estimation and enhance the robustness of the method. We used in vivo experimental datasets to evaluate the imaging performance of the proposed method. Results show that the proposed method significantly improves the imaging quality of uPDI compared to delay-and-sum (DAS) and coherence factor (CF) beamformers. Overall, the proposed method has the potential to become a reliable microvascular imaging technique.
Compared to pixelated detector, monolithic detector has better performance in sensitivity, light collection efficiency and cost. In PET detector, photon detector arrangement is of critical importance, which can influence detector performance significantly. In this study, three monolithic PET detector designs with different photon detector arrangement are proposed to improve spatial resolution and resolution uniformity. The PET detector is based on a $21\times 21\times 21 \mathrm {m}\mathrm {m}^{3}$ LYSO crystal and SiPM (SensL MicroFJ-30035). To improve detector performance with a reasonable number of SiPM, we proposed three different photon detector arrangements: Dual Ended (top and bottom: 5x5 array), Flexible Design A (top and bottom: 4x4 array, lateral: 2x2 array) and Flexible Design B (top and bottom: 3x3 array, lateral: 2x4 array). The Single Ended and Six Ended arrangement were also evaluated as reference. The solid angle criterion (SAC) is designed to evaluate spatial performance with less computation amounts, comparing with Cramer-Rao lower bound (CRLB). The Single Ended, Dual Ended and Flexible Design B detectors were realized to be evaluated in the preliminary experiment. The simulation results show that mean CRLB of Dual Ended, Flexible Design A and Flexible Design B are respectively 0.362, 0.363 and 0.325 mm in x/y direction, and 0.316, 0.331 and 0.325 mm in z direction. The SAC shows a strong correlation with CRLB. The preliminary experiment shows the spatial resolution of Flexible Design Bx/y:2.88 mm,z:5.16mm) is best, comparing with Single Ended (x/y:3.21 mm, z:5.88mm) and Dual Ended (x/y:3.05mm, z: 6.23mm). Flexible Design B has best resolution uniformity in both simulation and experiment. In conclusion, the simulation and experiment results proved that spatial performance of monolithic detector can be improved by optimizing the photon detector arrangement. SAC is a good simple evaluation criterion for spatial performance, which need less computation amounts compared with CLRB.
Preterm birth causes over 50% of neonatal deaths with high incidences ranging from 4% to 16% across countries. The short-term and long-term complications, especially the nervous system sequela, of preterm neonates brought a heavy burden to families and society. Timely clinical intervention is important to reduce poor outcome and prognoses. Cerebral microvascular development is associated with functional development. In this study, we explore the cerebral microvascular development by visualizing the cerebral microvessels of preterm and full-term neonates with different gestational ages (GAs) using ultrafast power Doppler imaging (uPDI) technique. Microvascular density is used as the evaluation index to quantitatively assess the cerebral microvessels. Statistical results on 83 preterm neonates and 13 full-term neonates suggest that the cerebral microvessels develop better with GA increases.
Abstract The current study presents superposition‐based concurrent multiscale approaches for porodynamics, capable of capturing related physical phenomena, such as soil liquefaction and dynamic hydraulic fracture branching, across different spatial length scales. Two scenarios are considered: superposition of finite element discretizations with varying mesh densities, and superposition of peridynamics (PD) and finite element method (FEM) to handle discontinuities like strain localization and cracks. The approach decomposes the acceleration and the rate of change in pore water pressure into subdomain solutions approximated by different models, allowing high‐fidelity models to be used locally in regions of interest, such as crack tips or shear bands, without neglecting the far‐field influence represented by low‐fidelity models. The coupled stiffness, mass, compressibility, permeability, and damping matrices were derived based on the superposition‐based current multiscale framework. The proposed FEM‐FEM porodynamic coupling approach was validated against analytical or numerical solutions for one‐ and two‐dimensional dynamic consolidation problems. The PD‐FEM porodynamic coupling model was applied to scenarios like soil liquefaction‐induced shear strain accumulation near a low‐permeability interlayer in a layered deposit and dynamic hydraulic fracturing branching. It has been shown that the coupled porodynamic model offers modeling flexibility and efficiency by taking advantage of FEM in modeling complex domains and the PD ability to resolve discontinuities.
The 5G communication system has experienced a substantial expansion of the spectrum, which poses higher requirements to radio frequency (RF) filters in enhancing their operating frequencies and bandwidths. To this end, this work focused on solving the filtering scheme for challenging 5G n77 and n78 bands and successfully implemented the corresponding spurious-free surface acoustic wave (SAW) filters exploiting large-coupling shear horizontal (SH) modes based on X-cut LiNbO3 (LN)/silicon carbide (SiC) heterostructure. Here, we initially investigated the suppression methods for spurious modes theoretically and experimentally and summarized an effective normalized LN thickness ( [Formula: see text] range of 0.15-0.30 for mitigating Rayleigh modes and higher order modes, as well as tilted interdigital transducers (IDT) by about 24° for eliminating transverse modes. Resonators with wavelengths ( λ) from 0.95 to [Formula: see text] were also fabricated, showing a scalable resonance from 2.48 to 4.21 GHz without any in-band ripple. Two filters completely meeting 5G n77 and n78 full bands were finally constructed, showing center frequencies ( fc) of 3763 and 3560 MHz, 3-dB fractional bandwidths (FBW) of 24.8% and 15.6%, and out-of-band (OoB) rejections of 18.7 and 28.1 dB, respectively. This work reveals that X-LN/SiC heterostructure is a promising underpinning material for SAW filters in 5G commercial applications.
<p>(a) Hela cells or (b) A549 cells stably expressing histone H2B-RFP were incubated with 10 μM of PIP3. At different time points, cells were harvested, stained, and imaged. Scale bar, 50 μm. (c) Nuclear localization of PIP3 in A549 cells. Scale bar, 10 μm.</p>
Recently, deep learning-based methods have been established to denoise the low-count positron emission tomography (PET) images and predict their standard-count image counterparts, which could achieve reduction of injected dosage and scan time, and improve image quality for equivalent lesion detectability and clinical diagnosis. In clinical settings, the majority scans are still acquired using standard injection dose with standard scan time. In this work, we applied a 3D U-Net network to reduce the noise of standard-count PET images to obtain the virtual-high-count (VHC) PET images for identifying the potential benefits of the obtained VHC PET images.The training datasets, including down-sampled standard-count PET images as the network input and high-count images as the desired network output, were derived from 27 whole-body PET datasets, which were acquired using 90-min dynamic scan. The down-sampled standard-count PET images were rebinned with matched noise level of 195 clinical static PET datasets, by matching the normalized standard derivation (NSTD) inside 3D liver region of interests (ROIs). Cross-validation was performed on 27 PET datasets. Normalized mean square error (NMSE), peak signal to noise ratio (PSNR), structural similarity index (SSIM), and standard uptake value (SUV) bias of lesions were used for evaluation on standard-count and VHC PET images, with real-high-count PET image of 90 min as the gold standard. In addition, the network trained with 27 dynamic PET datasets was applied to 195 clinical static datasets to obtain VHC PET images. The NSTD and mean/max SUV of hypermetabolic lesions in standard-count and VHC PET images were evaluated. Three experienced nuclear medicine physicians evaluated the overall image quality of randomly selected 50 out of 195 patients' standard-count and VHC images and conducted 5-score ranking. A Wilcoxon signed-rank test was used to compare differences in the grading of standard-count and VHC images.The cross-validation results showed that VHC PET images had improved quantitative metrics scores than the standard-count PET images. The mean/max SUVs of 35 lesions in the standard-count and true-high-count PET images did not show significantly statistical difference. Similarly, the mean/max SUVs of VHC and true-high-count PET images did not show significantly statistical difference. For the 195 clinical data, the VHC PET images had a significantly lower NSTD than the standard-count images. The mean/max SUVs of 215 hypermetabolic lesions in the VHC and standard-count images showed no statistically significant difference. In the image quality evaluation by three experienced nuclear medicine physicians, standard-count images and VHC images received scores with mean and standard deviation of 3.34±0.80 and 4.26 ± 0.72 from Physician 1, 3.02 ± 0.87 and 3.96 ± 0.73 from Physician 2, and 3.74 ± 1.10 and 4.58 ± 0.57 from Physician 3, respectively. The VHC images were consistently ranked higher than the standard-count images. The Wilcoxon signed-rank test also indicated that the image quality evaluation between standard-count and VHC images had significant difference.A DL method was proposed to convert the standard-count images to the VHC images. The VHC images had reduced noise level. No significant difference in mean/max SUV to the standard-count images was observed. VHC images improved image quality for better lesion detectability and clinical diagnosis.
Enhancing the central frequency (fc) and bandwidth (BW) and reducing insertion loss (IL) are essential steps in surface acoustic wave (SAW) filter applications in the 5G era. With this in mind, we construct a 32° Y-X LiNbO3(300 nm)/SiO2(300 nm)/poly-Si(1 μm)/Si heterostructure to avoid both acoustic leakage through the waveguide effect and electrical loss through the introduction of a poly-Si layer. By separately modulating the electrode thicknesses of series and parallel resonators, the spurious modes can be mitigated out of the filter passband, preventing them from negatively impacting the filter characteristics. Moreover, to reduce Ohmic loss, an optimized design for an Al/Cu/Ti multilayer electrode is proposed as a replacement for the Cu/Ti electrode resonators built on Al/Cu/Ti electrodes provide a high resonance frequency of 3.76 GHz, a large electromechanical coupling coefficient of 23%, and a maximum quality factor of 1510 (twice that of the Cu/Ti electrodes). Finally, SAW filters with an fc of 3728 MHz and a 3-dB BW of 1052 MHz are implemented, with IL of 0.92 dB. The achieved specifications demonstrates that one-chip SAW filter is expected to become n77 band filtering solution.
High-quality motion estimation is essential for ultrasound elastography (USE). Traditional motion estimation algorithms based on speckle tracking such as normalized cross correlation (NCC) or regularization such as global ultrasound elastography (GLUE) are time-consuming. In order to reduce the computational cost and ensure the accuracy of motion estimation, many convolutional neural networks have been introduced into USE. Most of these networks such as radio-frequency modified pyramid, warping and cost volume network (RFMPWC-Net) are supervised and need many ground truths as labels in network training. However, the ground truths are laborious to collect for USE. In this study, we proposed a MaskFlownet-based unsupervised convolutional neural network (MF-UCNN) for fast and high-quality motion estimation in USE. The inputs to MF-UCNN are the concatenation of RF, envelope, and B-mode images before and after deformation, while the outputs are the axial and lateral displacement fields. The similarity between the predeformed image and the warped image (i.e., the postdeformed image compensated by the estimated displacement fields) and the smoothness of the estimated displacement fields were incorporated in the loss function. The network was compared with modified pyramid, warping and cost volume network (MPWC-Net)++, RFMPWC-Net, GLUE, and NCC. Results of simulations, breast phantom, and in vivo experiments show that MF-UCNN obtains higher signal-to-noise ratio (SNR) and higher contrast-to-noise ratio (CNR). MF-UCNN achieves high-quality motion estimation with significantly reduced computation time. It is unsupervised and does not need any ground truths as labels in the training, and, thus, has great potential for motion estimation in USE.
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