IEEE transactions on ultrasonics, ferroelectrics, and frequency control最新文献_第9页

Advancing Single-Plane Wave Ultrasound Imaging With Implicit Multiangle Acoustic Synthesis via Deep Learning 通过深度学习，利用隐式多角度声学合成推进单面波超声波成像。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-02-13 DOI: 10.1109/TUFFC.2025.3541113

Yijia Liu;Na Jiang;Zhifei Dai;Miaomiao Zhang

{"title":"Advancing Single-Plane Wave Ultrasound Imaging With Implicit Multiangle Acoustic Synthesis via Deep Learning","authors":"Yijia Liu;Na Jiang;Zhifei Dai;Miaomiao Zhang","doi":"10.1109/TUFFC.2025.3541113","DOIUrl":"10.1109/TUFFC.2025.3541113","url":null,"abstract":"Plane wave imaging (PWI) is pivotal in medical ultrasound (US), prized for its ultrafast capabilities essential for real-time physiological monitoring. Traditionally, enhancing image quality in PWI has necessitated an increase in the number of plane waves (PWs), unfortunately compromising its hallmark high frame rates. To fully leverage the frame rate advantage of PWI, existing deep-learning-based methods often use single-PW as the sole input for training strategies to replicate multi-PWs compounding results. However, these typically fail to capture the intricate information provided by steered waves. In response, we have developed a sophisticated architecture that implicitly integrates multiangle information by generating and dynamically combining virtual steered PWs within the network. Using deep learning (DL) techniques, this system creates virtual steered waves from the single primary input view, simulating a limited number of steering angles. These virtual PWs are then expertly merged with actual single-PW data through an advanced attention mechanism. Through implicit multiangle acoustic synthesis, our approach achieves the high-quality output typically associated with extensive multiangle compounding. Rigorously evaluated on datasets acquired from simulations, experimental phantoms, and in vivo targets, our method has demonstrated superior performance over traditional single-PW strategies by providing more stable, reliable, and robust imaging outcomes. It excels in restoring detailed speckle patterns and diagnostic characteristics crucial for in vivo imaging, thereby offering a promising advancement in PWI technology without sacrificing speed. The code of the network is publicly available at <uri>https://github.com/yijiaLiu12/Implicit-Plane-Wave-Synthesis</uri>.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 4","pages":"479-497"},"PeriodicalIF":3.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Publication Information IEEE超音波学、铁电学与频率控制论文集

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-02-11 DOI: 10.1109/TUFFC.2025.3534645

引用次数: 0

Time-Sharing Acoustic Tweezers for Parallel Manipulation of Multiple Particles 分时声学镊子并行操作多个粒子。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-02-10 DOI: 10.1109/TUFFC.2025.3540512

Juan Zhou;Laixin Huang;Min Su;Zhiqiang Zhang;Weibao Qiu;Fei Li;Hairong Zheng

{"title":"Time-Sharing Acoustic Tweezers for Parallel Manipulation of Multiple Particles","authors":"Juan Zhou;Laixin Huang;Min Su;Zhiqiang Zhang;Weibao Qiu;Fei Li;Hairong Zheng","doi":"10.1109/TUFFC.2025.3540512","DOIUrl":"10.1109/TUFFC.2025.3540512","url":null,"abstract":"Holographic acoustic tweezers have various biomedical applications due to their ability to flexibly and rapidly synthesize acoustic fields for manipulating single or multiple particles. Existing multiparticle manipulation techniques are usually realized by precisely designing the incident wave’s phase distribution to synthesize a complex and steady-state acoustic field containing multiple acoustic trapping beams. However, interference effects between multiple beams tend to produce artifacts that trap particles in unwanted positions, limiting accuracy, and the number of manipulated particles. In addition, those techniques can only holistically manipulate multiple particles, namely, lacking parallel working ability. In this study, we proposed a time-sharing acoustic tweezer method to achieve the manipulation of multiple particles by rapidly switching individual trapping beams, minimizing interference artifacts. We applied this method to a 256-element phased-array acoustic tweezer system with designed ultrasonic pulse sequences to synthesize a single focused, twin trap, and vortex beam, enabling the pseudo-parallel manipulation of multiple particles in 3-D space at a beam switching frequency of ≥10 kHz. The experiments on polydimethylsiloxane particles ranging from micrometers to millimeters in diameter demonstrated that up to 96 particles can be successfully trapped and assembled into a 2-D lattice. Different numbers of particles were also patterned into dynamic contours, such as sinusoidal vibration (ten particles) and butterfly flapping (24 particles). In addition, the trapped multiple particles can also be rotated around their respective orbits. The proposed technique improved the number of objects dynamically manipulated in a parallel manner, advancing holographic acoustic tweezers and their applications.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 3","pages":"380-389"},"PeriodicalIF":3.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Remote Super-Resolution Mapping of Wave Fields 波场的远程超分辨率映射。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-02-04 DOI: 10.1109/TUFFC.2025.3538607

Jian-Yu Lu

{"title":"Remote Super-Resolution Mapping of Wave Fields","authors":"Jian-Yu Lu","doi":"10.1109/TUFFC.2025.3538607","DOIUrl":"10.1109/TUFFC.2025.3538607","url":null,"abstract":"Mapping wave field in space has many applications such as optimizing design of radio antennas, improving and developing ultrasound transducers, and planning and monitoring the treatment of tumors using high-intensity focused ultrasound (HIFU). Currently, there are methods that can map wave fields remotely or locally. However, there are limitations to these methods. For example, when mapping the wave fields remotely, the spatial resolution is limited due to a poor diffraction-limited resolution of the receiver, especially when the f-number of the receiver is large. To map the wave fields locally, the receiver is either subject to damage in hazardous environments (corrosive media, high temperature, high wave intensity, and so on) or difficult to be placed inside an object. To address these limitations, in this article, the point spread function (PSF)-modulation super-resolution imaging method was applied to map pulse ultrasound wave fields remotely at a high spatial resolution, overcoming the diffraction limit of a focused receiver. For example, to map a pulse ultrasound field of a full-width-at-half-maximum (FWHM) beamwidth of 1.24 mm at the focal distance of a transmitter, the FWHM beamwidths of the super-resolution mapping of the pulse wave field with a spherical glass modulator of 0.7 mm diameter at two receiver angles (0° and 45°) were about 1.13 and 1.22 mm, respectively, which were close to the theoretical value of 1.24 mm and were much smaller than the diffraction-limited resolution (1.81 mm) of the receiver. Without using the super-resolution method to remotely map the same pulse wave field, the FWHM beamwidth was about 2.06 mm. For comparison, the FWHM beamwidth obtained with a broadband (1–20 MHz) and 0.6-mm-diameter polyvinylidene fluoride (PVDF) needle hydrophone was about 1.41 mm. In addition to the focused pulse ultrasound wave field, a pulse Bessel beam near the transducer surface was mapped remotely with the super-resolution method, which revealed high spatial frequency components of the beam.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 3","pages":"370-379"},"PeriodicalIF":3.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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MM-UKAN++: A Novel Kolmogorov–Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation 基于Kolmogorov-Arnold网络的u形网络超声图像分割。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-02-04 DOI: 10.1109/TUFFC.2025.3539262

Boheng Zhang;Haorui Huang;Yi Shen;Mingjian Sun

{"title":"MM-UKAN++: A Novel Kolmogorov–Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation","authors":"Boheng Zhang;Haorui Huang;Yi Shen;Mingjian Sun","doi":"10.1109/TUFFC.2025.3539262","DOIUrl":"10.1109/TUFFC.2025.3539262","url":null,"abstract":"Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (ROIs) in US images is essential for enhancing the efficiency of clinical and robot-assisted diagnosis. However, US images suffer from low contrast, fuzzy boundaries, and significant scale variations in ROIs. Existing convolutional neural network (CNN)-based and transformer-based methods struggle with model efficiency and explainability. To address these challenges, we introduce MM-UKAN++, a novel U-shaped network based on Kolmogorov-Arnold networks (KANs). MM-UKAN++ leverages multilevel KAN layers as the encoder and decoder within the U-network architecture and incorporates an innovative multidimensional attention mechanism to refine skip connections by weighting features from frequency-channel and spatial perspectives. In addition, the network effectively integrates multiscale information, fusing outputs from different scale decoders to generate precise segmentation predictions. MM-UKAN++ achieves higher segmentation accuracy with lower computational cost and outperforms other mainstream methods on several open-source datasets for US image segmentation tasks, including achieving 69.42% IoU, 81.30% Dice, and 3.31 mm HD in the BUSI dataset with 3.17 G floating point of operations (FLOPs) and 9.90 M parameters. The excellent performance on our automatic carotid artery US scanning and diagnostic system further proves the speed and accuracy of MM-UKAN++. Besides, the good performance in other medical image segmentation tasks reveals the promising applications of MM-UKAN++. The code is available on GitHub.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 4","pages":"498-514"},"PeriodicalIF":3.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging 基于深度学习的超分辨率超声对比成像的波形特性研究。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-01-30 DOI: 10.1109/TUFFC.2025.3537298

Rienk Zorgdrager;Nathan Blanken;Jelmer M. Wolterink;Michel Versluis;Guillaume Lajoinie

{"title":"Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging","authors":"Rienk Zorgdrager;Nathan Blanken;Jelmer M. Wolterink;Michel Versluis;Guillaume Lajoinie","doi":"10.1109/TUFFC.2025.3537298","DOIUrl":"10.1109/TUFFC.2025.3537298","url":null,"abstract":"Resolving arterial flows is essential for understanding cardiovascular pathologies, improving diagnosis, and monitoring patient condition. Ultrasound contrast imaging uses microbubbles to enhance the scattering of the blood pool, allowing for real-time visualization of blood flow. Recent developments in vector flow imaging further expand the imaging capabilities of ultrasound by temporally resolving fast arterial flow. The next obstacle to overcome is the lack of spatial resolution. Super-resolved ultrasound images can be obtained by deconvolving radiofrequency (RF) signals before beamforming, breaking the link between resolution and pulse duration. Convolutional neural networks (CNNs) can be trained to locally estimate the deconvolution kernel and consequently super-localize the microbubbles directly within the RF signal. However, microbubble contrast is highly nonlinear, and the potential of CNNs in microbubble localization has not yet been fully exploited. Assessing deep learning-based deconvolution performance for nontrivial imaging pulses is therefore essential for successful translation to a practical setting, where the signal-to-noise ratio (SNR) is limited, and transmission schemes should comply with safety guidelines. In this study, we train CNNs to deconvolve RF signals and localize the microbubbles driven by harmonic pulses, chirps, or delay-encoded pulse trains. Furthermore, we discuss potential hurdles for in vitro and in vivo super-resolution by presenting preliminary experimental results. We find that, whereas the CNNs can accurately localize microbubbles for all pulses, a short imaging pulse offers the best performance in noise-free conditions. However, chirps offer a comparable performance without noise, but they are more robust to noise and outperform all other pulses in low-SNR conditions.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 4","pages":"427-439"},"PeriodicalIF":3.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Delivery of Cavitation Therapy With a Modified Clinical Scanner: In Vitro Evaluation 用改良的临床扫描仪进行空化治疗：体外评估。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-01-29 DOI: 10.1109/TUFFC.2025.3536932

Lance H. De Koninck;Kaleb S. Vuong;Seonghun Shin;Jeffry E. Powers;Michalakis A. Averkiou

{"title":"Delivery of Cavitation Therapy With a Modified Clinical Scanner: In Vitro Evaluation","authors":"Lance H. De Koninck;Kaleb S. Vuong;Seonghun Shin;Jeffry E. Powers;Michalakis A. Averkiou","doi":"10.1109/TUFFC.2025.3536932","DOIUrl":"10.1109/TUFFC.2025.3536932","url":null,"abstract":"In this study, we design and implement pulses [1.67 MHz, 20–1000 cycles, 0.8–2.5 MPa, and 5–100 ms pulse repetition time (PRT)] suitable for microbubble cavitation treatments with a phased array of a clinical ultrasound scanner. A range of acoustic parameters was evaluated in a tissue-mimicking phantom with suspended Sonazoid microbubbles. Hydrophone measurements were used to optimize the transmit beamforming. A passive cavitation detection (PCD) system was designed to measure the microbubble scattered signals over a 1 s exposure. Postprocessing of the scattered signals evaluated frequency content to extract broadband energy and calculate the inertial cavitation dose (ICD). ICD was maximized at 1000 cycles (maximum pulse length), 5 ms (fastest firing rate), and 2.5 MPa peak negative pressure (PNP) (maximum pressure). Inertial cavitation was only sustained for about three pulses (out of hundreds fired) occurring within the first 100 ms of treatment. Temporal analysis of the first 1000-cycle pulse revealed that broadband energy is sustained for the entire pulse. We also demonstrate that while inertial cavitation is possible with clinically available pulse wave Doppler settings, ICD can be significantly increased using the new conditions suggested in this work. We have delivered successful image-guided cavitation treatment after modifying a clinical scanner and monitored the cavitation dose with a PCD system on a gel phantom with suspended microbubbles. We plan to apply this technique in vivo in animal tumor models next. This work demonstrates the first implementation of long, high-pressure pulses on a clinical scanner that users can optimize for cavitation treatments.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 3","pages":"351-361"},"PeriodicalIF":3.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Frequency-Domain Decoding of Cascaded Dual- Polarity Waves for Ultrafast Ultrasound Imaging 超快超声成像级联双极性波频域解码。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-01-28 DOI: 10.1109/TUFFC.2025.3534429

Charlotte L. Nawijn;Joosje M. K. de Bakker;Tim Segers;Chris L. de Korte;Michel Versluis;Anne E. C. M. Saris;Guillaume Lajoinie

{"title":"Frequency-Domain Decoding of Cascaded Dual- Polarity Waves for Ultrafast Ultrasound Imaging","authors":"Charlotte L. Nawijn;Joosje M. K. de Bakker;Tim Segers;Chris L. de Korte;Michel Versluis;Anne E. C. M. Saris;Guillaume Lajoinie","doi":"10.1109/TUFFC.2025.3534429","DOIUrl":"10.1109/TUFFC.2025.3534429","url":null,"abstract":"Ultrafast plane-wave (PW) ultrasound imaging is a versatile tool that has become increasingly relevant for blood flow imaging using speckle tracking but suffers from a low signal-to-noise ratio (SNR). Cascaded dual-polarity wave (CDW) imaging can improve the SNR by transmitting pulse trains, which are subsequently decoded to recover the imaging resolution. However, the current decoding method (in the time domain) requires a set of two acquisitions, which introduces motion artifacts that result in incorrect speckle tracking at high flow velocities. Here, we evaluate an inverse filtering approach that uses frequency-domain decoding to decode acquisitions independently. Experiments using a disk phantom show that frequency-domain decoding of a four-pulse train achieves an SNR gain of up to 4.2 dB, versus 5.9 dB for conventional decoding. The benefit of frequency-domain decoding for flow quantification is assessed through experiments performed with a rotating disk phantom and a parabolic flow, and through matching linear simulations. Both CDW methods improve the tracking accuracy compared to single PW imaging. Time-domain decoding outperforms frequency-domain decoding in low SNR conditions and low velocities (<inline-formula> <tex-math>$leq 0.25$ </tex-math></inline-formula> m/s), as a result of the higher SNR gain. In contrast, frequency-domain decoding outperforms time-domain decoding for high peak velocities in imaging of the rotating disk (1 m/s) and of the parabolic flow (2 m/s), when significant scatterer motion between acquisitions causes imperfect time-domain decoding. Its ability to decode individual acquisitions makes the used frequency-domain decoding of CDW (F-CDW) a promising approach to improve the SNR and thereby the accuracy of flow quantification at high velocities.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 3","pages":"321-337"},"PeriodicalIF":3.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10856850","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Publication Information IEEE超音波学、铁电学与频率控制论文集

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-01-27 DOI: 10.1109/TUFFC.2025.3529339

引用次数: 0

Spatially Weighted Fidelity and Regularization Terms for Attenuation Imaging 衰减成像的空间加权保真度和正则化项。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-01-27 DOI: 10.1109/TUFFC.2025.3534660

Sebastian Merino;Roberto Lavarello

{"title":"Spatially Weighted Fidelity and Regularization Terms for Attenuation Imaging","authors":"Sebastian Merino;Roberto Lavarello","doi":"10.1109/TUFFC.2025.3534660","DOIUrl":"10.1109/TUFFC.2025.3534660","url":null,"abstract":"Quantitative ultrasound (QUS) holds promise in enhancing diagnostic accuracy. For attenuation imaging, the regularized spectral log difference (RSLD) can generate accurate local attenuation maps. However, the performance of the method degrades when significant changes in backscatter amplitude occur. Variations in the technique were introduced involving a weighted approach to backscatter regularization, which, however, is not effective when changes in both attenuation and backscatter are present. This study introduces a novel approach that incorporates an L1-norm for backscatter regularization and spatially varying weights for both fidelity and regularization terms. The weights are calculated from an initial estimation of backscatter changes. Comparative analyses with simulated, phantom, and clinical data were performed. When changes in backscatter and attenuation occur, the proposed approach reduced the lowest root mean square error by up to 73%. It also improved the contrast-to-noise ratio (CNR) by a factor of 4.4 on average compared with previously available methods, considering the simulated and phantom data. In vivo results from healthy livers, thyroid nodules, and a breast tumor further confirm its effectiveness. In the liver, it is shown to be effective at reducing artifacts of attenuation images. In thyroid and breast tumors, the method demonstrated an enhanced CNR and better consistency of the attenuation measurements with the posterior acoustic enhancement. Overall, this approach offers promise for enhancing ultrasound attenuation imaging by helping differentiate tissue characteristics that may indicate pathology.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 3","pages":"338-350"},"PeriodicalIF":3.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143541853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0