IEEE transactions on ultrasonics, ferroelectrics, and frequency control最新文献_第2页

Synthetic vs. Classic Data Augmentation: Impacts on Breast Ultrasound Image Classification. 合成与经典数据增强：对乳腺超声图像分类的影响。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-05-01 DOI: 10.1109/TUFFC.2025.3566340

Yasamin Medghalchi, Niloufar Zakariaei, Arman Rahmim, Ilker Hacihaliloglu

{"title":"Synthetic vs. Classic Data Augmentation: Impacts on Breast Ultrasound Image Classification.","authors":"Yasamin Medghalchi, Niloufar Zakariaei, Arman Rahmim, Ilker Hacihaliloglu","doi":"10.1109/TUFFC.2025.3566340","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3566340","url":null,"abstract":"The effectiveness of Deep Neural Networks (DNNs) for ultrasound image analysis depends on the availability and accuracy of training data. However, large-scale data collection and annotation, particularly in medical fields, is often costly and time-consuming, especially when healthcare professionals are already burdened with their clinical responsibilities. Ensuring that a model remains robust across different imaging conditions-such as variations in ultrasound devices and manual transducer operation-is crucial in ultrasound image analysis. Data augmentation is a widely used solution, as it increases both the size and diversity of datasets, thereby enhancing the generalization performance of DNNs. With the advent of generative networks like Generative Adversarial Networks (GAN) and diffusion-based models, synthetic data generation has emerged as a promising augmentation technique. However, comprehensive studies comparing classic and generative method-based augmentation methods are lacking, particularly in ultrasound-based breast cancer imaging, where variability in breast density, tumor morphology, and operator skill poses significant challenges. This study aims to compare the effectiveness of classic and generative network-based data augmentation techniques in improving the performance and robustness of breast ultrasound image classification models. Specifically, we seek to determine whether the computational intensity of generative networks is justified in data augmentation. This analysis will provide valuable insights into the role and benefits of each technique in enhancing diagnostic accuracy of DNN for breast cancer diagnosis. The code for this work will be available at https://github.com/yasamin-med/SCDA.git.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144003684","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

Layer-Wise Speed-of-Sound Estimation and Beamforming of Segmented Media. 分段媒体的分层声速估计和波束形成。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-29 DOI: 10.1109/TUFFC.2025.3565273

Pat De La Torre, Di Xiao, Alfred C H Yu

{"title":"Layer-Wise Speed-of-Sound Estimation and Beamforming of Segmented Media.","authors":"Pat De La Torre, Di Xiao, Alfred C H Yu","doi":"10.1109/TUFFC.2025.3565273","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3565273","url":null,"abstract":"Speed-of-sound (SoS) is a fundamental acoustic property of tissues that is essential for ultrasound image beamforming. The SoS can also act as a quantitative biomarker for pathology in tissue. Typically, the beamforming SoS is assumed to be 1540 m/s for human imaging, but it may be imprecise for imaging scenarios with inhomogeneous tissue. In this work, we present a novel framework for multi-layer SoS estimation and propose a SoS-aware (SoSA) beamformer to realize high-quality ultrasound imaging. Our framework consists of three core steps: segmentation of the media layers, sequential estimation of each layer's SoS assuming intra-layer homogeneity, and SoSA beamforming based on the estimated SoS map. We validated our algorithm in vitro, ex vivo, and in vivo in comparison to through-transmission SoS measurements. Across 126 stacked agar phantom experiments (pairwise combinations of six staircase phantoms with different SoS values), the average SoS estimation error of our framework was 4.9 m/s over the top layers and 1.6 m/s over bottom layers. In nine stacked bovine and porcine sample experiments, we achieved an average error of 2.7 m/s with improved point target lateral resolution of 32.5% compared to conventional beamforming with a nominal SoS of 1540 m/s. When indirectly evaluated over five human calves, our algorithm achieved a mean error of 7.9 m/s for the average calf SoS. Also, in human quadriceps imaging scenarios, our proposed framework showed image quality enhancements with improved visibility of the fascicle structure. Overall, our new technique improves.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143965397","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

Generation of High-Order Modes in Resonators Based on Aperiodically Poled Piezoelectric Film Stacks. 基于非周期极化压电薄膜堆的谐振腔高阶模的产生。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-29 DOI: 10.1109/TUFFC.2025.3565505

Natalya F Naumenko

{"title":"Generation of High-Order Modes in Resonators Based on Aperiodically Poled Piezoelectric Film Stacks.","authors":"Natalya F Naumenko","doi":"10.1109/TUFFC.2025.3565505","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3565505","url":null,"abstract":"Aperiodically Poled Piezoelectric Film (APPF) stacks have recently been proposed as an extension of Periodically Poled Piezoelectric Film (P3F) structures, a promising platform for the expansion of radio frequency filters into cm-and mm-wave frequency bands. Variations in the thicknesses between the layers of the APPF stacks enable the generation of higher-order modes typically absent in P3F structures and provide additional options for the design of high-frequency filters. In this study, a simple model is proposed to optimize the thickness ratio in a three-layered structure for the generation or suppression of any mode. Its validity was confirmed by the rigorously simulated admittance functions of the resonators based on optimal structures and comparison with experimental data. The coupling coefficients of modes A1-A11 laterally excited in the 128?YX LN-based three-layered stacks were calculated as functions of the continuously varying thickness ratios. These dependencies can be used for the selection of APPF stacks with simultaneous enhancement of the primary mode and suppression of the undesired modes. In the analyzed LN plates of thickness 600 nm, the electromechanical coupling coefficients of the modes A5 and A7 generated at the frequencies 14.6 GHz and 20.4 GHz increased from 2.4% to 17% and from 1.2% to 9.9%, respectively, when the inverted middle layer of the optimal thickness was introduced, whereas the nearest modes were suppressed. The appearance of spurious symmetric modes in the previously reported experimental P3F structures was explained and the geometry of the stacks required to avoid these spurious modes is described.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020113","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

Single Crystal Row-Column Array based Rat Brain 3-D Ultrasound Localization Microscopy. 基于单晶行列阵列的大鼠脑三维超声定位显微镜。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-23 DOI: 10.1109/TUFFC.2025.3563809

Qiandong Sun, Shilin Hou, Rui He, Yapeng Fu, Jiamin Wu, Jiyan Dai, Kailiang Xu

{"title":"Single Crystal Row-Column Array based Rat Brain 3-D Ultrasound Localization Microscopy.","authors":"Qiandong Sun, Shilin Hou, Rui He, Yapeng Fu, Jiamin Wu, Jiyan Dai, Kailiang Xu","doi":"10.1109/TUFFC.2025.3563809","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3563809","url":null,"abstract":"Ultrasound localization microscopy (ULM) enables imaging of cerebral vasculature at microscopic scale with deep penetration. However, conventional two-dimensional (2D) ULM suffers from the elevation projection and cannot capture the outof- plane vessels. Recently developed volumetric ULM overcomes the limitations by providing isotropic resolution and enabling comprehensive visualization of the microvascular architecture in three dimensions. In this study, we developed a single crystal 128 + 128 row-column addressed (RCA) probe centered at 13 MHz, with a bandwidth of 80% and a large aperture of 15.36 × 15.36 mm2, which is suitable for volumetric imaging of small animals and superficial organs. Three-dimensional rendering of superresolved vascular density and velocity maps was performed to visualize the cerebral vasculature at an improved spatial resolution of 24.7 μm. The developed methodology demonstrated the performance of single-crystal RCA based in vivo volumetric imaging of micro-cerebrovascular, highlighting its high potential for studying neurodegenerative diseases, intracranial aneurysms, and stroke.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968357","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 : 2025-04-22 DOI: 10.1109/TUFFC.2025.3559747

引用次数: 0

Deep Learning to Localize Photoacoustic Sources in Three Dimensions: Theory and Implementation. 三维光声源定位的深度学习：理论与实现。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-22 DOI: 10.1109/TUFFC.2025.3562313

Mardava R Gubbi, Muyinatu A Lediju Bell

{"title":"Deep Learning to Localize Photoacoustic Sources in Three Dimensions: Theory and Implementation.","authors":"Mardava R Gubbi, Muyinatu A Lediju Bell","doi":"10.1109/TUFFC.2025.3562313","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3562313","url":null,"abstract":"Surgical tool tip localization and tracking are essential components of surgical and interventional procedures. The cross sections of tool tips can be considered as acoustic point sources to achieve these tasks with deep learning applied to photoacoustic channel data. However, source localization was previously limited to the lateral and axial dimensions of an ultrasound transducer. In this paper, we developed a novel deep learning-based three-dimensional (3D) photoacoustic point source localization system using an object detection-based approach extended from our previous work. In addition, we derived theoretical relationships among point source locations, sound speeds, and waveform shapes in raw photoacoustic channel data frames. We then used this theory to develop a novel deep learning instance segmentation-based 3D point source localization system. When tested with 4,000 simulated, 993 phantom, and 1,983 ex vivo channel data frames, the two systems achieved F1 scores as high as 99.82%, 93.05%, and 98.20%, respectively, and Euclidean localization errors (mean ± one standard deviation) as low as 1.46±1.11 mm, 1.58±1.30 mm, and 1.55±0.86 mm, respectively. In addition, the instance segmentation-based system simultaneously estimated sound speeds with absolute errors (mean ± one standard deviation) of 19.22±26.26 m/s in simulated data and standard deviations ranging 14.6-32.3 m/s in experimental data. These results demonstrate the potential of the proposed photoacoustic imaging-based methods to localize and track tool tips in three dimensions during surgical and interventional procedures.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144006190","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

First-Order Speckle Statistics for the Detection of Microstructural Anisotropy. 用于显微结构各向异性检测的一阶散斑统计。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-21 DOI: 10.1109/TUFFC.2025.3562784

Alexandra M Christensen, Timothy J Hall, Helen Feltovich, Ivan M Rosado-Mendez

{"title":"First-Order Speckle Statistics for the Detection of Microstructural Anisotropy.","authors":"Alexandra M Christensen, Timothy J Hall, Helen Feltovich, Ivan M Rosado-Mendez","doi":"10.1109/TUFFC.2025.3562784","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3562784","url":null,"abstract":"Speckle statistics estimation is a useful quantitative ultrasound tool for characterizing tissue microstructure. However, because of their elongated geometry, fibrillar tissue components like collagen may not be described well by speckle statistics models. The purpose of this study is to perform a systematic analysis of the effects of microstructural anisotropy on speckle statistics estimation. We created phantoms made of wool fibers to correlate speckle statistics estimates to elongated scatterer geometries. Phantoms were attached to a calibrated spring to induce fiber alignment by applying a known tension. Ultrasonic beams were steered to 0, ±5, and ±10 degrees. Nakagami and homodyned K distribution parameters were calculated from each steered acquisition. Applying tension (0 to 3±0.2 N) induced alignment in the wool fibers such that speckle statistics estimates exhibited increased dependence on beam steering angle. Whereas an isotropically scattering phantom exhibited 4%, 55%, 25% and 17% total changes in Nakagami m, Nakagami Ω, homodyned K α, and homodyned K k metrics (respectively) over all steering angles with reference to the 0 degree estimate, changes of 35%, 177%, 151%, and 23% were observed in wool fiber phantoms. The same experiment was repeated in the Achilles tendon of a human subject (28%, 190%, 140%, and 53%) and in the cervix of a Rhesus macaque (9%, 76%, 58%, and 11%) to demonstrate sensitivity in vivo. This study demonstrates how speckle statistics parameters can be used to measure the degree of alignment of anisotropic acoustic scatterers separately from spatial density.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020044","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

Combining Deep Data-driven and Physics-inspired Learning for Shear Wave Speed Estimation in Ultrasound Elastography. 结合深度数据驱动和物理启发学习超声弹性成像中横波速度估计。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-16 DOI: 10.1109/TUFFC.2025.3561599

Ali K Z Tehrani, Scott Schoen, Ion Candel, Yuyang Gu, Peng Guo, Kai Thomenius, Theodore T Pierce, Michael Wang, Rimon Tadross, Mike Washburn, Hassan Rivaz, Anthony E Samir

{"title":"Combining Deep Data-driven and Physics-inspired Learning for Shear Wave Speed Estimation in Ultrasound Elastography.","authors":"Ali K Z Tehrani, Scott Schoen, Ion Candel, Yuyang Gu, Peng Guo, Kai Thomenius, Theodore T Pierce, Michael Wang, Rimon Tadross, Mike Washburn, Hassan Rivaz, Anthony E Samir","doi":"10.1109/TUFFC.2025.3561599","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3561599","url":null,"abstract":"Shear wave elastography (SWE) provides quantitative markers for tissue characterization by measuring shear wave speed (SWS), which reflects tissue stiffness. SWE uses an acoustic radiation force pulse sequence to generate shear waves that propagate laterally through tissue with transient displacements. These waves travel perpendicular to the applied force, and their displacements are tracked using high-frame-rate ultrasound. Estimating the SWS map involves two main steps: speckle tracking and SWS estimation. Speckle tracking calculates particle velocity by measuring RF/IQ data displacement between adjacent firings, while SWS estimation methods typically compare particle velocity profiles of samples that are laterally a few millimeters apart. Deep learning (DL) methods have gained attention for SWS estimation, often relying on supervised training using simulated data. However, these methods may struggle with real-world data, which can differ significantly from simulated training data, potentially leading to artifacts in the estimated SWS map. To address this challenge, we propose a physics-inspired learning approach that utilizes real data without known SWS values. Our method employs an adaptive unsupervised loss function, allowing the network to train with real noisy data to minimize the artifacts and improve the robustness. We validate our approach using experimental phantom data and in vivo liver data from two human subjects, demonstrating enhanced accuracy and reliability in SWS estimation compared to conventional and supervised methods. This hybrid approach leverages the strengths of both data-driven and physics-inspired learning, offering a promising solution for more accurate and robust SWS mapping in clinical applications.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143976014","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

A Deep Reinforcement Learning Based Region-Specific Beamformer for Sparse Arrays 3D Ultrasound Imaging. 基于深度强化学习的区域特定波束形成器用于稀疏阵列三维超声成像。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-15 DOI: 10.1109/TUFFC.2025.3560872

Mohamed Tamraoui, Herve Liebgott, Emmanuel Roux

{"title":"A Deep Reinforcement Learning Based Region-Specific Beamformer for Sparse Arrays 3D Ultrasound Imaging.","authors":"Mohamed Tamraoui, Herve Liebgott, Emmanuel Roux","doi":"10.1109/TUFFC.2025.3560872","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3560872","url":null,"abstract":"Sparse arrays offer several advantages over other element reduction techniques for 3D ultrasound imaging. However, the large inter-element spacing in these arrays results in high sidelobe-related artifacts, which significantly degrade image quality and limit their application in 3D ultrasound imaging. Adaptive beamformers have been proposed to mitigate sidelobe-related artifacts, but they often degrade speckle texture quality, resulting in unnaturally dark images. To overcome these limitations, we propose RSB-Net, a region-specific beamformer based on deep reinforcement learning. RSB-Net adaptively selects the most suitable beamformer for each pixel of the image, applying adaptive beamforming in regions dominated by sidelobe artifacts and delay-and-sum beamforming in regions where speckle texture should be preserved. The effectiveness of RSB-Net was validated on both simulated and experimental synthetic transmit aperture RF datasets with a new designed sparse array prototype. On simulated data, RSB-Net achieved significant gains, with improvements of 52.81 dB in contrast ratio and 0.65 in generalized contrast-to-noise ratio compared to DAS beamforming. In experimental tissue-mimicking phantom data, RSB-Net demonstrated similar performance, achieving gains of 51.01 dB and 0.64 respectively. These results highlight the potential of RSB-Net as a robust and effective solution for high-quality B-mode 3D ultrasound imaging using 2D sparse arrays, advancing the standardization of 3D ultrasound in clinical settings by enhancing anatomical visualization, reducing operator dependency, and improving measurement accuracy for lesions and calcifications.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968259","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

A High Frequency Ultrasound Endoscope for Minimally Invasive Spine Surgery. 用于微创脊柱手术的高频超声内窥镜。

IF 3 2区工程技术

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Pub Date : 2025-04-10 DOI: 10.1109/TUFFC.2025.3559870

M Nicole MacMullin, Theresa Gu, Thomas G Landry, Nicholas Campbell, Sean D Christie, Jeremy A Brown

{"title":"A High Frequency Ultrasound Endoscope for Minimally Invasive Spine Surgery.","authors":"M Nicole MacMullin, Theresa Gu, Thomas G Landry, Nicholas Campbell, Sean D Christie, Jeremy A Brown","doi":"10.1109/TUFFC.2025.3559870","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3559870","url":null,"abstract":"The transition to minimally invasive spinal surgery over traditional open procedures requires the development of imaging techniques that meet the size constraints. Due to size restrictions associated with minimally invasive spine surgery, current imaging techniques are largely limited to microscopy, which is only capable of line-of-sight imaging of the tissue surface. A miniature, high-resolution ultrasound imaging endoscope has been developed as a potential alternative imaging method that would enable intra-operative guidance. We have designed and developed a 30 MHz miniature, 64-element, high-resolution imaging endoscope using PIN-PMT-PT single crystal as the piezoelectric substrate. The packaged probe had cross-sectional dimensions of 3.8 mm x 4.2 mm and a length of 14 cm. Two editions of the endoscope were created with a forward-facing and 40⁰ angle to enable visualization of structures during a medial and lateral approach, respectively. The probe was combined with a custom imaging system that produced real-time images with a field of view ranging between ±32⁰ and an image depth of 15 mm. The two-way axial resolution was measured to be 38 μm based on the -6 dB width of the pulse envelope. The -6 dB lateral resolution was measured to be 113 μm, 131 μm, and 158 μm at steering angles of 0⁰, 12⁰, and 25⁰ respectively, which were close to the simulated values of 106 μm, 118 μm and 144 μm. Preliminary clinical imaging studies successfully demonstrated the visualization of pertinent spinal anatomy during minimally invasive surgeries. The imaging probe was also able to demonstrate compression and decompression of nerve roots, supporting its potential use as a clinical tool.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144012604","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