Ultrasonics最新文献_第2页

Reconstruction of reflection ultrasound computed tomography with sparse transmissions using conditional generative adversarial network 利用条件生成对抗网络重建稀疏传输的反射超声计算机断层扫描。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-15 DOI: 10.1016/j.ultras.2024.107486

Zhaohui Liu , Xiang Zhou , Hantao Yang , Qiude Zhang , Liang Zhou , Yun Wu , Quanquan Liu , Weicheng Yan , Junjie Song , Mingyue Ding , Ming Yuchi , Wu Qiu

Ultrasound computed tomography (UCT) has attracted increasing attention due to its potential for early breast cancer diagnosis and screening. Synthetic aperture imaging is a widely used means for reflection UCT image reconstruction, due to its ability to produce isotropic and high-resolution anatomical images. However, obtaining fully sampled UCT data from all directions over multiple transmissions is a time-consuming scanning process. Even though sparse transmission strategy could mitigate the data acquisition complication, image quality reconstructed by traditional Delay and Sum (DAS) methods may degrade substantially. This study presents a deep learning framework based on a conditional generative adversarial network, UCT-GAN, to efficiently reconstruct reflection UCT image from sparse transmission data. The evaluation experiments using breast imaging data in vivo show that the proposed UCT-GAN is able to generate high-quality reflection UCT images when using 8 transmissions only, which are comparable to that reconstructed from the data acquired by 512 transmissions. Quantitative assessment in terms of peak signal-to-noise ratio (PSNR), normalized mean square error (NMSE), and structural similarity index measurement (SSIM) show that the proposed UCT-GAN is able to efficiently reconstruct high-quality reflection UCT images from sparsely available transmission data, outperforming several other methods, such as RED-GAN, DnCNN-GAN, BM3D. In the experiment of 8-transmission sparse data, the PSNR is 29.52 dB, and the SSIM is 0.7619. The proposed method has the potential of being integrated into the UCT imaging system for clinical usage.

超声波计算机断层扫描（UCT）因其在早期乳腺癌诊断和筛查方面的潜力而受到越来越多的关注。合成孔径成像技术能够生成各向同性的高分辨率解剖图像，因此被广泛用于超声计算机断层扫描图像的反射重建。然而，通过多次传输从各个方向获取完全采样的 UCT 数据是一个耗时的扫描过程。尽管稀疏传输策略可以减轻数据采集的复杂性，但通过传统的延迟与求和（DAS）方法重建的图像质量可能会大幅下降。本研究提出了一种基于条件生成对抗网络（UCT-GAN）的深度学习框架，可从稀疏传输数据中高效地重建反射 UCT 图像。使用乳房活体成像数据进行的评估实验表明，所提出的 UCT-GAN 仅使用 8 次传输就能生成高质量的反射 UCT 图像，其质量可与 512 次传输数据重建的图像相媲美。从峰值信噪比（PSNR）、归一化均方误差（NMSE）和结构相似性指数测量（SSIM）等方面进行的定量评估表明，所提出的 UCT-GAN 能够从稀疏的传输数据中有效地重建高质量的反射 UCT 图像，其性能优于 RED-GAN、DnCNN-GAN 和 BM3D 等其他几种方法。在 8 个传输稀疏数据的实验中，PSNR 为 29.52 dB，SSIM 为 0.7619。该方法有望集成到 UCT 成像系统中用于临床。

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引用次数: 0

A physics-based acoustic emission energy method for mixed-mode impact damage prediction of composite laminates 基于物理的声发射能量法，用于复合材料层压板的混合模式冲击损伤预测

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-12 DOI: 10.1016/j.ultras.2024.107490

Jingjing He , Fan Yang , Haixu Wang , Xiaojun Sun , Yu Zhu , Yaokun Wang , Xuefei Guan

In-service composite laminates are susceptible to impact-induced damage, which can substantially reduce its integrity and service life. The damage prediction remains a great challenge due to mixed damage modes and varying damage patterns. This study develops a novel acoustic emission (AE) energy method for predicting damage areas under three typical damage modes. Laboratory testing of composite laminate specimens subject to quasi-static indentation is performed in conjunction with in-situ AE monitoring to acquire AE data. By bridging two sets of energy formulations developed, namely, the one that correlates the damage area and the released strain energy of each damage mode and another that relates the released strain energy to the AE energy, an analytical model for predicting damage areas using AE energy components is derived. Proper signal procedure procedures are established to extract the energy components from AE monitoring data, and numerical and testing data are used to calibrate the model parameters. The effectiveness of the proposed model is further validated by comparing the prediction results of the damage areas with the actual damage areas of specimens tested under different indentation depths. The result indicates that the proposed AE energy method can yield reliable predictions of the damage area under mixed damage modes.

使用中的复合材料层压板很容易受到冲击引起的损坏，这会大大降低其完整性和使用寿命。由于混合损伤模式和不同的损伤模式，损伤预测仍然是一个巨大的挑战。本研究开发了一种新型声发射（AE）能量方法，用于预测三种典型损坏模式下的损坏区域。在对受到准静态压痕的复合材料层压板试样进行实验室测试的同时，还进行了原位 AE 监测，以获取 AE 数据。通过将所开发的两套能量公式（即将每种损坏模式的损坏面积和释放应变能相关联的公式，以及将释放应变能与 AE 能量相关联的公式）连接起来，得出了使用 AE 能量成分预测损坏面积的分析模型。建立了从 AE 监测数据中提取能量分量的适当信号程序，并使用数值和测试数据来校准模型参数。通过比较损伤面积的预测结果和不同压痕深度下测试试样的实际损伤面积，进一步验证了所提模型的有效性。结果表明，所提出的 AE 能量方法可以可靠地预测混合损伤模式下的损伤面积。

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引用次数: 0

Research on the fusion imaging method of sign coherence and time reversal for Lamb wave sparse array λ波稀疏阵列符号相干与时间反转融合成像方法研究

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-11 DOI: 10.1016/j.ultras.2024.107489

Liu-Jia Sun, Qing-Bang Han, Cheng Yin, Qi-Lin Jin, Kao Ge

Time-reversal imaging struggles to detect plate-like structures due to interference from Lamb wave mode conversion and the processing demands, leading to less effective outcomes. This paper proposes a sign coherence factor and time reversal fusion (SCF-TR) imaging method based on amplitude and phase estimation. This method removes the coherence of array signals during signal reversal and refocusing. It reintroduces the sign coherence component to reduce interference from non-target scattered waves and partially overcome the constraints imposed by the Rayleigh criterion. The method allows imaging at a resolution smaller than the wavelength of Lamb and enhances the quality of the resulting images. In addition, a sparse array design utilizing the White Shark Optimisation Algorithm (WSO) is proposed to streamline the SCF-TR calculation process. This design utilizes sparse full matrix data to improve imaging efficiency. The experimental results show that for single blind hole defects, the SCF-TR method improves the array performance metrics and signal-to-noise ratio by 22.46% and 42.50%, respectively, compared to the TR method. For multiple asymmetric blind hole defects, when the defect size exceeds the resolution threshold, SCF-TR accurately reflects the position and morphology of defects smaller than the wavelength. When the defect size is below the resolution threshold, SCF-TR achieves super-resolution imaging. The sparse array designed using the White Shark Optimization algorithm demonstrates good sidelobe characteristics, effectively reducing sidelobe noise without reducing the array aperture. Moreover, the SCF-TR imaging time is reduced by approximately half while maintaining imaging accuracy.

由于 Lamb 波模式转换的干扰和处理要求，时间反转成像在检测板状结构方面很吃力，导致效果不佳。本文提出了一种基于振幅和相位估计的符号相干因子和时间反转融合（SCF-TR）成像方法。这种方法能消除信号反转和重新聚焦时阵列信号的相干性。它重新引入了符号相干分量，以减少非目标散射波的干扰，并部分克服了瑞利准则带来的限制。该方法允许在小于 Lamb 波长的分辨率下成像，并提高了所得图像的质量。此外，还提出了一种利用白鲨优化算法（WSO）的稀疏阵列设计，以简化 SCF-TR 计算过程。这种设计利用稀疏全矩阵数据来提高成像效率。实验结果表明，对于单个盲孔缺陷，SCF-TR 方法与 TR 方法相比，阵列性能指标和信噪比分别提高了 22.46% 和 42.50%。对于多个不对称盲孔缺陷，当缺陷尺寸超过分辨率阈值时，SCF-TR 能准确反映小于波长的缺陷的位置和形态。当缺陷尺寸低于分辨率阈值时，SCF-TR 可实现超分辨率成像。利用白鲨优化算法设计的稀疏阵列具有良好的侧叶特性，能在不减小阵列孔径的情况下有效降低侧叶噪声。此外，在保持成像精度的同时，SCF-TR 的成像时间缩短了约一半。

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引用次数: 0

Low-intensity pulsed ultrasound improves metabolic dysregulation in obese mice by suppressing inflammation and extracellular matrix remodeling 低强度脉冲超声通过抑制炎症和细胞外基质重塑改善肥胖小鼠的代谢失调

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-10 DOI: 10.1016/j.ultras.2024.107488

Min He , Hong Zhu , Jingsong Dong , Wenzhen Lin , Boyi Li , Ying Li , Dean Ta

Chronic inflammation in white adipose tissue is crucial in obesity and related metabolic disorders. Low-intensity pulsed ultrasound (LIPUS) is renowned for its anti-inflammatory effects as a non-invasive treatment, yet its precise role in obesity has been uncertain. Our study investigates the therapeutic effect of LIPUS and its underlying mechanism on obesity in mice, thereby offering a novel approach for non-invasive treatment of obesity and associated metabolic disorders for human. Male C57BL/6J mice aged 10 weeks were fed a high-fat diet (HFD) for 8 weeks to establish obesity model, then underwent 8 weeks of LIPUS (frequency: 1.0 MHz, duty cycle: 20 %, I_sata: 58–61 mW/cm², 20 min per day) stimulation of the epididymal white adipose tissue. Fat and lean mass were measured using nuclear magnetic resonance (NMR), while energy homeostasis was evaluated using metabolic cages. Insulin resistance was assessed using glucose tolerance tests (GTT) and insulin tolerance tests (ITT). Regulatory mechanisms were explored using RNA sequencing. Results showed that LIPUS significantly reduced obesity markers in obese mice, including body and adipose tissue weight, and improved insulin resistance, without affecting food intake. RNA sequencing showed 250 up-regulated and 351 down-regulated genes between HFD-LIPUS group and HFD-Sham group, suggesting anti-inflammatory action. Quantitative PCR confirmed reduced pro-inflammatory gene expression and macrophage infiltration in eWAT. Gene set enrichment analysis showed decreased NF-κB signaling and extracellular matrix-receptor interactions in LIPUS-treated mice. Thus, LIPUS effectively mitigates metabolic dysregulation in HFD-induced obesity through inflammation suppression and extracellular matrix remodeling, which provides a potential physical therapy for metabolic syndrome in clinic.

白色脂肪组织中的慢性炎症是肥胖和相关代谢紊乱的关键因素。低强度脉冲超声（LIPUS）作为一种非侵入性治疗方法，以其抗炎作用而闻名，但它在肥胖症中的确切作用还不确定。我们的研究调查了 LIPUS 对小鼠肥胖症的治疗效果及其内在机制，从而为人类提供了一种非侵入性治疗肥胖症及相关代谢紊乱的新方法。对年龄为 10 周的雄性 C57BL/6J 小鼠喂食高脂饮食（HFD）8 周以建立肥胖模型，然后对附睾白色脂肪组织进行为期 8 周的 LIPUS（频率：1.0 MHz，占空比：20%，等效功率：58-61 mW/cm2，每天 20 分钟）刺激。使用核磁共振（NMR）测量脂肪和瘦肉质量，使用代谢笼评估能量平衡。胰岛素抵抗通过葡萄糖耐量试验（GTT）和胰岛素耐量试验（ITT）进行评估。利用 RNA 测序探索了调控机制。结果表明，LIPUS能明显降低肥胖小鼠的肥胖指标，包括体重和脂肪组织重量，并改善胰岛素抵抗，而不影响食物摄入量。RNA测序显示，HFD-LIPUS组和HFD-Sham组分别有250个基因上调，351个基因下调，这表明LIPUS具有抗炎作用。定量 PCR 证实，eWAT 中的促炎基因表达和巨噬细胞浸润减少。基因组富集分析表明，LIPUS 治疗小鼠的 NF-κB 信号转导和细胞外基质-受体相互作用减少。因此，LIPUS 通过抑制炎症和细胞外基质重塑，有效缓解了高氟酸膳食诱导的肥胖症代谢失调，为临床治疗代谢综合征提供了一种潜在的物理疗法。

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引用次数: 0

Damage detection and localization in plate-like structures using sideband peak count (SPC) technique 利用边带峰值计数（SPC）技术检测和定位板状结构中的损伤。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-05 DOI: 10.1016/j.ultras.2024.107485

Bo Hu , Tribikram Kundu

This paper addresses the critical issue of detecting and localizing damage in plate-like structures, which are commonly encountered in aerospace, marine and other engineering applications. To address this challenge, the current study introduces the sideband peak count (SPC) technique as the foundation for diagnostic imaging for damage detection in plate structures. The proposed damage detection algorithm requires only a limited number of sensor responses, streamlining the detection process. It does not rely on a reference baseline, thereby enhancing its efficiency and accuracy. This approach enables rapid and precise identification of damage and its location within the plate structure. To validate the effectiveness and applicability of the proposed method, finite element simulation results are utilized. These results demonstrate the capability of the proposed technique to accurately detect and localize damage, providing a promising solution for enhancing the structural health monitoring of plate-like structures in various engineering domains.

本文探讨了在航空航天、海洋和其他工程应用中常见的板状结构中检测和定位损伤的关键问题。为应对这一挑战，本研究引入了边带峰值计数（SPC）技术，作为板状结构损伤检测诊断成像的基础。所提出的损伤检测算法只需要数量有限的传感器响应，从而简化了检测过程。它不依赖参考基线，从而提高了效率和准确性。这种方法能够快速、精确地识别板结构中的损伤及其位置。为了验证所提方法的有效性和适用性，我们使用了有限元模拟结果。这些结果表明，所提出的技术具有准确检测和定位损伤的能力，为在各种工程领域中加强板状结构的结构健康监测提供了一个前景广阔的解决方案。

引用次数: 0

A semi-analytical framework for predicting far-field responses of complex elastic waves emitters 预测复杂弹性波发射器远场响应的半分析框架。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-03 DOI: 10.1016/j.ultras.2024.107483

Siddhesh Raorane, Tadeusz Stepinski, Pawel Packo

Applications of guided waves in various fields of engineering and science rely on elastic wave emitters for wave generation. Accurate prediction and understanding of the far-field responses of these wave emitters are crucial for the reliable and efficient application of guided waves-based technologies. In this paper, we propose a novel semi-analytical framework capable of predicting the far-field response of complex wave emitters of arbitrary shape and internal structure in any type of substrate. This framework is general, and is not confined to specific methods, enhancing its versatility. We applied the proposed semi-analytical framework to predict the directivity patterns of two different macro-fiber composite transducers, accurately modeled using their exact topologies. The framework’s validity was experimentally confirmed by comparing the predicted directivity patterns with the results obtained from experimental measurements.

导波在各个工程和科学领域的应用都依赖于弹性波发射器来产生波。准确预测和理解这些波发射器的远场响应，对于可靠、高效地应用基于导波的技术至关重要。在本文中，我们提出了一个新颖的半分析框架，能够预测任何类型基底中任意形状和内部结构的复杂波发射器的远场响应。该框架具有通用性，不局限于特定的方法，从而增强了其通用性。我们应用所提出的半分析框架预测了两种不同的宏纤维复合传感器的指向性模式，并使用它们的精确拓扑结构进行了精确建模。通过将预测的指向性模式与实验测量结果进行比较，实验证实了该框架的有效性。

引用次数: 0

Beamforming-integrated neural networks for ultrasound imaging 用于超声波成像的波束成形集成神经网络。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-10-03 DOI: 10.1016/j.ultras.2024.107474

Di Xiao, Alfred C.H. Yu

Sparse matrix beamforming (SMB) is a computationally efficient reformulation of delay-and-sum (DAS) beamforming as a single sparse matrix multiplication. This reformulation can potentially dovetail with machine learning platforms like TensorFlow and PyTorch that already support sparse matrix operations. In this work, using SMB principles, we present the development of beamforming-integrated neural networks (BINNs) that can rationally infer ultrasound images directly from pre-beamforming channel-domain radiofrequency (RF) datasets. To demonstrate feasibility, a toy BINN was first designed with two 2D-convolution layers that were respectively placed both before and after an SMB layer. This toy BINN correctly updated kernel weights in all convolution layers, demonstrating efficiency in both training (PyTorch – 133 ms, TensorFlow – 22 ms) and inference (PyTorch – 4 ms, TensorFlow – 5 ms). As an application demonstration, another BINN with two RF-domain convolution layers, an SMB layer, and three image-domain convolution layers was designed to infer high-quality B-mode images in vivo from single-shot plane-wave channel RF data. When trained using 31-angle compounded plane wave images (3000 frames from 22 human volunteers), this BINN showed mean-square logarithmic error improvements of 21.3 % and 431 % in the inferred B-mode image quality respectively comparing to an image-to-image convolutional neural network (CNN) and an RF-to-image CNN with the same number of layers and learnable parameters (3,777). Overall, by including an SMB layer to adopt prior knowledge of DAS beamforming, BINN shows potential as a new type of informed machine learning framework for ultrasound imaging.

稀疏矩阵波束成形（SMB）是对延迟与和（DAS）波束成形的一种计算高效的重构，是一种单一的稀疏矩阵乘法。这种重构有可能与 TensorFlow 和 PyTorch 等已经支持稀疏矩阵运算的机器学习平台对接。在这项工作中，我们利用 SMB 原理开发了波束成形集成神经网络（BINN），它可以直接从预波束成形信道域射频（RF）数据集合理推断超声图像。为了证明其可行性，我们首先设计了一个玩具 BINN，它有两个二维卷积层，分别位于 SMB 层之前和之后。这个玩具 BINN 正确更新了所有卷积层的内核权重，在训练（PyTorch - 133 毫秒，TensorFlow - 22 毫秒）和推理（PyTorch - 4 毫秒，TensorFlow - 5 毫秒）方面都表现出高效率。作为应用演示，我们设计了另一个具有两个射频域卷积层、一个 SMB 层和三个图像域卷积层的 BINN，用于从单发平面波通道射频数据推断高质量的活体 B 模式图像。在使用 31 角复合平面波图像（来自 22 名人体志愿者的 3000 帧图像）进行训练时，与具有相同层数和可学习参数（3,777）的图像到图像卷积神经网络（CNN）和射频到图像 CNN 相比，该 BINN 所推断的 B 型图像质量的均方对数误差分别提高了 21.3% 和 431%。总之，通过加入一个采用 DAS 波束成形先验知识的 SMB 层，BINN 显示出作为一种新型超声成像知情机器学习框架的潜力。

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引用次数: 0

A new theoretical model for high-order harmonics of SH0 mode ultrasonic guided waves based on magnetostrictive mechanism 基于磁致伸缩机制的 SH0 模式超声导波高阶谐波新理论模型。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-09-30 DOI: 10.1016/j.ultras.2024.107480

Huan Wang , Xiucheng Liu , Bin Wu , Xiang Gao , Yao Liu , Cunfu He

In recent years, it was found that magnetostrictive ultrasonic guided wave transducers experimentally excited nonlinear harmonic components under a certain combination of dynamic and static magnetic fields. However, a satisfactory model for the relevant excitation mechanisms is not available. In this study, a new magnetostrictive guided wave excitation model was established and the causes for harmonics generation were analyzed. In addition, the calculation results of the model were obtained under different magnetic field parameters. We firstly changed the calculation conditions of magnetostrictive strain in the model and then theoretically calculated the odd and even harmonics of SH₀ mode ultrasonic guided waves for the first time. Furthermore, the accuracy of the model was experimentally verified. By changing the strength ratio of the dynamic magnetic field to the static magnetic field (H_D/H_S), the excitation amplitudes of odd and even harmonics could be regulated with a magnetostrictive sensor. As the ratio of H_D/H_S increased, the normalized amplitude of the second harmonic firstly increased and then decreased, whereas the normalized amplitude of the third harmonic showed an exponential growth with different curvatures. This study enriched the theory of magnetostrictive guided wave excitation and provided a theoretical basis for the applications of magnetostrictive sensors.

近年来，人们发现磁致伸缩超声导波换能器在一定的动静态磁场组合下会激发非线性谐波成分。然而，目前还没有一个令人满意的相关激励机制模型。本研究建立了一个新的磁致伸缩导波激励模型，并分析了谐波产生的原因。此外，还获得了该模型在不同磁场参数下的计算结果。我们首先改变了模型中磁致伸缩应变的计算条件，然后首次从理论上计算了 SH0 模式超声导波的奇次谐波和偶次谐波。此外，还通过实验验证了模型的准确性。通过改变动态磁场与静态磁场的强度比（HD/HS），可以利用磁致伸缩传感器调节奇次谐波和偶次谐波的激励幅值。随着 HD/HS 比值的增大，二次谐波的归一化振幅先增大后减小，而三次谐波的归一化振幅则呈现出不同曲率的指数增长。这项研究丰富了磁致伸缩导波激励理论，为磁致伸缩传感器的应用提供了理论依据。

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引用次数: 0

Compensation of system nonlinearity in the measurement of acoustic nonlinearity parameters 测量声学非线性参数时的系统非线性补偿。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-09-30 DOI: 10.1016/j.ultras.2024.107484

Jiung Yoo , Dong-Gi Song , Kyung-Young Jhang

The acoustic nonlinearity parameter is determined from the amplitudes of the fundamental and second harmonic component of the acoustic wave propagating through the material. However, the generally used through-transmission based measurements with PZT transducers contain high system nonlinearity, so that the received second harmonic component includes an extra component caused by the transducer, which significantly decrease the reliability of measurements. In this study, we proposed a novel method to reduce the system nonlinearity in the conventional through-transmission based measurements by adding a simple process in which the transmitting and receiving transducers are in direct contact without a specimen. The proposed method was experimentally validated for two materials, Al6061-T6 and Fused Silica. For both materials, several specimens with different thickness were prepared, and the measurement results showed that the magnitude of the second harmonic was proportional to the thickness, but there was an offset due to system nonlinearity. On the other hand, after applying the proposed technique, the offsets were greatly reduced, and furthermore, this performance was maintained even when the transducer setup was changed, and the ratio of nonlinearity parameters measured for the two materials was in good agreement with the known literature value.

声学非线性参数是根据声波在材料中传播时的基波和二次谐波分量的振幅确定的。然而，通常使用的基于 PZT 换能器的穿透式测量包含较高的系统非线性，因此接收到的二次谐波分量包含了由换能器引起的额外分量，这大大降低了测量的可靠性。在这项研究中，我们提出了一种新方法，通过添加一个简单的过程，使发射和接收传感器在没有试样的情况下直接接触，从而降低传统的穿透式测量中的系统非线性。所提出的方法在两种材料（Al6061-T6 和熔融石英）上进行了实验验证。测量结果表明，二次谐波的大小与厚度成正比，但由于系统的非线性，存在偏移。另一方面，在应用所提出的技术后，偏移量大大减少，而且即使改变传感器的设置也能保持这种性能，两种材料测得的非线性参数比率与已知文献值非常一致。

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引用次数: 0

Image quality improvement in single plane-wave imaging using deep learning 利用深度学习提高单平面波成像的图像质量。

IF 3.8 2区物理与天体物理 Q1 ACOUSTICS

Ultrasonics

Pub Date : 2024-09-30 DOI: 10.1016/j.ultras.2024.107479

Kanta Miura , Hiromi Shidara , Takuro Ishii , Koichi Ito , Takafumi Aoki , Yoshifumi Saijo , Jun Ohmiya

In ultrasound image diagnosis, single plane-wave imaging (SPWI), which can acquire ultrasound images at more than 1000 fps, has been used to observe detailed tissue and evaluate blood flow. SPWI achieves high temporal resolution by sacrificing the spatial resolution and contrast of ultrasound images. To improve spatial resolution and contrast in SPWI, coherent plane-wave compounding (CPWC) is used to obtain high-quality ultrasound images, i.e., compound images, by coherent addition of radio frequency (RF) signals acquired by transmitting plane waves in different directions. Although CPWC produces high-quality ultrasound images, their temporal resolution is lower than that of SPWI. To address this problem, some methods have been proposed to reconstruct a ultrasound image comparable to a compound image from RF signals obtained by transmitting a small number of plane waves in different directions. These methods do not fully consider the properties of RF signals, resulting in lower image quality compared to a compound image. In this paper, we propose methods to reconstruct high-quality ultrasound images in SPWI by considering the characteristics of RF signal of a single plane wave to obtain ultrasound images with image quality comparable to CPWC. The proposed methods employ encoder–decoder models of 1D U-Net, 2D U-Net, and their combination to generate the high-quality ultrasound images by minimizing the loss that considers the point spread effect of plane waves and frequency spectrum of RF signals in training. We also create a public large-scale SPWI/CPWC dataset for developing and evaluating deep-learning methods. Through a set of experiments using the public dataset and our dataset, we demonstrate that the proposed methods can reconstruct higher-quality ultrasound images from RF signals in SPWI than conventional method.

在超声图像诊断中，单平面波成像（SPWI）能以超过 1000 fps 的速度获取超声图像，已被用于观察组织细节和评估血流。SPWI 通过牺牲超声图像的空间分辨率和对比度来实现高时间分辨率。为了提高 SPWI 的空间分辨率和对比度，采用了相干平面波复合（CPWC）技术，通过将从不同方向发射平面波获得的射频（RF）信号相干相加，获得高质量的超声图像，即复合图像。虽然 CPWC 能生成高质量的超声图像，但其时间分辨率低于 SPWI。为了解决这个问题，有人提出了一些方法，利用从不同方向发射少量平面波获得的射频信号重建与复合图像相当的超声图像。这些方法没有充分考虑射频信号的特性，导致图像质量低于复合图像。在本文中，我们提出了通过考虑单个平面波的射频信号特性来重建 SPWI 中高质量超声波图像的方法，以获得与 CPWC 图像质量相当的超声波图像。所提出的方法采用一维 U-网络、二维 U-网络的编码器-解码器模型及其组合，通过最小化损耗生成高质量超声图像，其中考虑了训练中平面波的点扩散效应和射频信号的频谱。我们还创建了一个公开的大规模 SPWI/CPWC 数据集，用于开发和评估深度学习方法。通过使用公共数据集和我们的数据集进行一系列实验，我们证明了与传统方法相比，我们提出的方法可以从 SPWI 中的射频信号重建更高质量的超声图像。

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引用次数: 0