Pub Date : 2025-07-17DOI: 10.1109/TUFFC.2025.3586556
Kathlyne Jayne B. Bautista;Emmanuel Cherin;Jianhua Yin;Elvira C. Vazquez Avila;F. Stuart Foster;Christine E. M. Demore;Paul A. Dayton
The acoustic angiography leverages the superharmonic response of microbubbles against linear tissue to generate 3-D maps of microvasculature. This contrast-enhanced ultrasound imaging approach uses dual-frequency (DF) transducers that transmit at frequencies less than 5 MHz and receive at frequencies three times or greater than the fundamental frequency to selectively detect microbubble signals. Previous iterations of the hardware were designed mainly to image preclinical models. In pilot clinical imaging studies, these transducers suffered from poor microbubble sensitivity and shallow imaging depths. Here, we investigate multiple DF transducers operating at varying transmit frequencies less than 2 MHz and center receive frequencies ranging from 7 to 18 MHz designed for deeper imaging and greater bubble sensitivity than earlier generation devices. We assess the superharmonic imaging (SpHI) performance of these transducers in vitro and in vivo by characterizing contrast sensitivity and resolution. We demonstrate improvements in sensitivity at lower transmit (<1 MHz) and receive (<10 MHz) frequencies, measuring contrast signal enhancement up to 31.8 dB. At these lower frequencies, we also achieve imaging depths up to 50–55 mm—the deepest application of acoustic angiography to date. These advances in imaging sensitivity and depth address the primary barriers to the clinical translation of acoustic angiography.
{"title":"Extending the Transmit and Receive Bandwidths of Dual-Frequency Transducers Toward Clinical Acoustic Angiography: In Vitro and In Vivo Studies","authors":"Kathlyne Jayne B. Bautista;Emmanuel Cherin;Jianhua Yin;Elvira C. Vazquez Avila;F. Stuart Foster;Christine E. M. Demore;Paul A. Dayton","doi":"10.1109/TUFFC.2025.3586556","DOIUrl":"10.1109/TUFFC.2025.3586556","url":null,"abstract":"The acoustic angiography leverages the superharmonic response of microbubbles against linear tissue to generate 3-D maps of microvasculature. This contrast-enhanced ultrasound imaging approach uses dual-frequency (DF) transducers that transmit at frequencies less than 5 MHz and receive at frequencies three times or greater than the fundamental frequency to selectively detect microbubble signals. Previous iterations of the hardware were designed mainly to image preclinical models. In pilot clinical imaging studies, these transducers suffered from poor microbubble sensitivity and shallow imaging depths. Here, we investigate multiple DF transducers operating at varying transmit frequencies less than 2 MHz and center receive frequencies ranging from 7 to 18 MHz designed for deeper imaging and greater bubble sensitivity than earlier generation devices. We assess the superharmonic imaging (SpHI) performance of these transducers in vitro and in vivo by characterizing contrast sensitivity and resolution. We demonstrate improvements in sensitivity at lower transmit (<1 MHz) and receive (<10 MHz) frequencies, measuring contrast signal enhancement up to 31.8 dB. At these lower frequencies, we also achieve imaging depths up to 50–55 mm—the deepest application of acoustic angiography to date. These advances in imaging sensitivity and depth address the primary barriers to the clinical translation of acoustic angiography.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 9","pages":"1222-1234"},"PeriodicalIF":3.7,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659107","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}
Pub Date : 2025-07-16DOI: 10.1109/TUFFC.2025.3589815
YiRang Shin;Bing-Ze Lin;Matthew R. Lowerison;Qi You;Pengfei Song
3-D ultrasound localization microscopy (ULM) enables comprehensive mapping of microvascular networks by providing micrometer-scale spatial resolution while avoiding projection errors inherent to 2-D ULM imaging. Current 3-D ULM techniques are based on linear pulse sequences combined with spatiotemporal filtering to distinguish microbubble flow from tissue signals. However, singular-value decomposition (SVD)-based filtering demonstrates poor performance in highly mobile organs, suppressing small vessels with slow blood flow along with tissue signals. While imaging based on nonlinear multipulse sequences can isolate microbubble signals regardless of tissue motion, achieving the high-volume acquisition rates required for 3-D ULM remains technically challenging. Here, we present Fast3D-amplitude modulation (AM) imaging, a 3-D nonlinear imaging sequence that achieves a high-volume acquisition rate (225 Hz) using a single 256-channel ultrasound system with a multiplexed 2-D matrix array. We also introduce a motion rejection algorithm that leverages localized microbubble positions to reject respiratory-induced motion artifacts. Fast3D-AM imaging achieved a superior contrast-to-tissue ratio (CTR) than Fast3D, exhibiting a 6.66-dB improvement in phantom studies. In an in vivo rat study, Fast3D-AM demonstrated higher CTR across all SVD cutoffs compared to Fast3D and preserved both major and microvascular structures in whole-organ kidney imaging.
{"title":"High-Volume Acquisition Rate Nonlinear Imaging Enables Robust 3-D Ultrasound Localization Microscopy","authors":"YiRang Shin;Bing-Ze Lin;Matthew R. Lowerison;Qi You;Pengfei Song","doi":"10.1109/TUFFC.2025.3589815","DOIUrl":"10.1109/TUFFC.2025.3589815","url":null,"abstract":"3-D ultrasound localization microscopy (ULM) enables comprehensive mapping of microvascular networks by providing micrometer-scale spatial resolution while avoiding projection errors inherent to 2-D ULM imaging. Current 3-D ULM techniques are based on linear pulse sequences combined with spatiotemporal filtering to distinguish microbubble flow from tissue signals. However, singular-value decomposition (SVD)-based filtering demonstrates poor performance in highly mobile organs, suppressing small vessels with slow blood flow along with tissue signals. While imaging based on nonlinear multipulse sequences can isolate microbubble signals regardless of tissue motion, achieving the high-volume acquisition rates required for 3-D ULM remains technically challenging. Here, we present Fast3D-amplitude modulation (AM) imaging, a 3-D nonlinear imaging sequence that achieves a high-volume acquisition rate (225 Hz) using a single 256-channel ultrasound system with a multiplexed 2-D matrix array. We also introduce a motion rejection algorithm that leverages localized microbubble positions to reject respiratory-induced motion artifacts. Fast3D-AM imaging achieved a superior contrast-to-tissue ratio (CTR) than Fast3D, exhibiting a 6.66-dB improvement in phantom studies. In an in vivo rat study, Fast3D-AM demonstrated higher CTR across all SVD cutoffs compared to Fast3D and preserved both major and microvascular structures in whole-organ kidney imaging.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 9","pages":"1199-1212"},"PeriodicalIF":3.7,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082392","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649310","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}
Pub Date : 2025-07-08DOI: 10.1109/TUFFC.2025.3586377
Vincent van de Schaft;Oisín Nolan;Ruud J. G. van Sloun
Ultrasound images formed by delay-and-sum (DAS) beamforming are plagued by artifacts that only clear up after compounding many transmissions. One promising way to mitigate this is posing imaging as an inverse problem. Inverse problem-based imaging approaches can yield high image quality with few transmits, but existing methods require a very fine image grid and are not robust to changes in measurement model parameters. We present inverse grid-free estimation of reflectivities (INFER), an off-grid and stochastic algorithm that finds a solution to the inverse scattering problem in ultrasound imaging. Our method jointly optimizes for the locations of the gridpoints, their reflectivities, and the speed of sound. This approach allows us to use fewer gridpoints than existing methods. At the same time, it obtains $2times $ –$3times $ higher far-field lateral resolution and 6%–68% higher generalized contrast-to-noise ratio (gCNR) on in vivo data, and it is robust to speed of sound changes of up to ±100 m/s. The use of stochastic optimization enables solving for multiple transmissions simultaneously without increasing the required memory or computational load per iteration. We show that our method works on both phantom and in vivo data and compares favorably against existing beamforming methods. The source code and the dataset to reproduce the results in this article are available at ww.w.github.com/vincentvdschaft/off-grid-ultrasound
{"title":"Off-Grid Ultrasound Imaging by Stochastic Optimization","authors":"Vincent van de Schaft;Oisín Nolan;Ruud J. G. van Sloun","doi":"10.1109/TUFFC.2025.3586377","DOIUrl":"10.1109/TUFFC.2025.3586377","url":null,"abstract":"Ultrasound images formed by delay-and-sum (DAS) beamforming are plagued by artifacts that only clear up after compounding many transmissions. One promising way to mitigate this is posing imaging as an inverse problem. Inverse problem-based imaging approaches can yield high image quality with few transmits, but existing methods require a very fine image grid and are not robust to changes in measurement model parameters. We present inverse grid-free estimation of reflectivities (INFER), an off-grid and stochastic algorithm that finds a solution to the inverse scattering problem in ultrasound imaging. Our method jointly optimizes for the locations of the gridpoints, their reflectivities, and the speed of sound. This approach allows us to use fewer gridpoints than existing methods. At the same time, it obtains <inline-formula> <tex-math>$2times $ </tex-math></inline-formula>–<inline-formula> <tex-math>$3times $ </tex-math></inline-formula> higher far-field lateral resolution and 6%–68% higher generalized contrast-to-noise ratio (gCNR) on in vivo data, and it is robust to speed of sound changes of up to ±100 m/s. The use of stochastic optimization enables solving for multiple transmissions simultaneously without increasing the required memory or computational load per iteration. We show that our method works on both phantom and in vivo data and compares favorably against existing beamforming methods. The source code and the dataset to reproduce the results in this article are available at <monospace>ww.w.github.com/vincentvdschaft/off-grid-ultrasound</monospace>","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 9","pages":"1245-1255"},"PeriodicalIF":3.7,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144583814","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}
Pub Date : 2025-07-07DOI: 10.1109/TUFFC.2025.3586460
Yi Zeng;Shixiao W. Jiang;Hui Zhu;Jinwei Li;Jianfeng Li;Fei Li;Shukuan Lu;Xiran Cai
While passive acoustic mapping (PAM) has been advanced for monitoring acoustic cavitation activity in focused ultrasound (FUS) therapy, achieving both real-time and high-quality imaging capabilities is still challenging. The angular spectrum (AS) method presents the most efficient algorithm for PAM, but it suffers from artifacts and low resolution due to the diffraction pattern of the imaging array. Data-adaptive beamformers suppress artifacts well, but their overwhelming computational complexity, more than two orders of magnitude higher than the classical time exposure acoustic (TEA) method, hinders their application in real time. In this work, we introduce the cross-correlated AS method to address the challenge. This method is based on cross-correlating the AS back-propagated wave fields, in the frequency domain (FD), measured by different apodized subapertures of the transducer array to provide the normalized cross-correlation coefficient (NCC) matrix for artifacts suppression. We observed that the spatial pattern of NCC matrix is variable, which can be utilized by the triple apodization with cross correlation (TAX) with AS scheme, namely, the AS-TAX method, for optimal artifacts suppression outcomes. Both the phantom and mouse tumor experiments showed that: 1) the AS-TAX method has comparable image quality as the data-adaptive beamformers, reducing the energy spread area (ESA) by 34.8%–65.0% and improving image signal-to-noise ratio (ISNR) by 10.6–14.4 dB compared to TEA; 2) it reduces the computational complexity by two orders of magnitude compared to TEA allowing millisecond-level image reconstruction speed with a parallel implementation; and 3) it can well map microbubble cavitation activity of different status (stable or inertial). The AS-TAX method represents a real-time approach to monitor cavitation-based FUS therapy with high image quality.
{"title":"High-Quality Passive Acoustic Mapping With the Cross-Correlated Angular Spectrum Method","authors":"Yi Zeng;Shixiao W. Jiang;Hui Zhu;Jinwei Li;Jianfeng Li;Fei Li;Shukuan Lu;Xiran Cai","doi":"10.1109/TUFFC.2025.3586460","DOIUrl":"10.1109/TUFFC.2025.3586460","url":null,"abstract":"While passive acoustic mapping (PAM) has been advanced for monitoring acoustic cavitation activity in focused ultrasound (FUS) therapy, achieving both real-time and high-quality imaging capabilities is still challenging. The angular spectrum (AS) method presents the most efficient algorithm for PAM, but it suffers from artifacts and low resolution due to the diffraction pattern of the imaging array. Data-adaptive beamformers suppress artifacts well, but their overwhelming computational complexity, more than two orders of magnitude higher than the classical time exposure acoustic (TEA) method, hinders their application in real time. In this work, we introduce the cross-correlated AS method to address the challenge. This method is based on cross-correlating the AS back-propagated wave fields, in the frequency domain (FD), measured by different apodized subapertures of the transducer array to provide the normalized cross-correlation coefficient (NCC) matrix for artifacts suppression. We observed that the spatial pattern of NCC matrix is variable, which can be utilized by the triple apodization with cross correlation (TAX) with AS scheme, namely, the AS-TAX method, for optimal artifacts suppression outcomes. Both the phantom and mouse tumor experiments showed that: 1) the AS-TAX method has comparable image quality as the data-adaptive beamformers, reducing the energy spread area (ESA) by 34.8%–65.0% and improving image signal-to-noise ratio (ISNR) by 10.6–14.4 dB compared to TEA; 2) it reduces the computational complexity by two orders of magnitude compared to TEA allowing millisecond-level image reconstruction speed with a parallel implementation; and 3) it can well map microbubble cavitation activity of different status (stable or inertial). The AS-TAX method represents a real-time approach to monitor cavitation-based FUS therapy with high image quality.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 10","pages":"1352-1363"},"PeriodicalIF":3.7,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144583813","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}
Pub Date : 2025-07-02DOI: 10.1109/TUFFC.2025.3585301
Hui Zhu;Yi Zeng;Jianfeng Li;Kailiang Xu;Xiran Cai
Real-time and 3-D monitoring of cavitation activity is critical for safe, effective, and controlled treatments in cavitation-based focused ultrasound (FUS) therapies. This 3-D monitoring capability is essential for detecting off-target cavitation events, particularly in at-risk structures and those occurring outside the plane of 2-D imaging. In this work, we demonstrate that using row-column arrays (RCAs) for 3-D passive acoustic mapping (PAM), which can be easily integrated into commercial ultrasound scanners compared to using hemispherical arrays or matrix arrays, represents a potent solution. For that, we propose the RCA-PAM method for image formation. This method deploys the angular spectrum (AS) method to back-propagate 3-D harmonic wave fields using the passively received cavitation signals by the RCA’s row and column apertures, respectively. Then, the 3-D PAM volume is obtained by integrating the cross-spectrum of the two wave fields over a selected bandwidth. To further reduce image artifacts, we combine AS with dual-apodization with cross correlation (AS-DAX) for wave field propagation. Our experiments showed that RCA-PAM achieved 0.04±0.07 mm source localization error and comparable image quality to the ones reconstructed for the matrix array (same aperture size). We realized over 40 volumes/second reconstruction speed for a volume sized $128,times , 128,times ,250$ voxels, using all frequency components in the RCA’s working bandwidth. We also demonstrate the seamless combination of RCA-PAM and B-mode imaging using the same RCA for 3-D monitoring of MB cavitation activity in a mouse tumor model. In summary, the use of RCAs for cavitation monitoring represents a promising avenue to minimize treatment risks in cavitation-based FUS therapies.
在以空泡为基础的聚焦超声（FUS）治疗中，空泡活动的实时和三维监测对于安全、有效和可控的治疗至关重要。这种3D监测能力对于检测脱靶空化事件至关重要，特别是在危险结构中以及发生在2D成像平面之外的空化事件。在这项工作中，我们证明了使用行列阵列（RCAs）进行3D被动声学测绘（PAM），与使用半球形阵列或矩阵阵列相比，它可以很容易地集成到商用超声扫描仪中，是一种有效的解决方案。为此，我们提出了RCA-PAM图像生成方法。该方法采用角谱（AS）方法，分别利用RCA的行孔和列孔被动接收的空化信号反向传播三维谐波场。然后，在选定的带宽范围内对两个波场的交叉谱进行积分，得到三维PAM体。为了进一步减少图像伪影，我们将AS与双重apodiization with cross-correlation （AS- dax）相结合进行波场传播。实验结果表明，RCA-PAM的源定位误差为0.04±0.07 mm，与相同孔径下重构的矩阵阵列的源定位误差相当。对于体积大小为128×128×250的体素，我们实现了超过40卷/秒的重建速度，使用了RCA工作带宽中的所有频率分量。我们还展示了RCA- pam和b模式成像的无缝结合，使用相同的RCA对小鼠肿瘤模型中的MB空化活动进行3D监测。总之，使用RCAs进行空化监测是一种很有希望的方法，可以将基于空化的FUS治疗的治疗风险降到最低。
{"title":"Real-Time 3-D Passive Acoustic Mapping for Row-Column Arrays With the Cross-Spectrum Method","authors":"Hui Zhu;Yi Zeng;Jianfeng Li;Kailiang Xu;Xiran Cai","doi":"10.1109/TUFFC.2025.3585301","DOIUrl":"10.1109/TUFFC.2025.3585301","url":null,"abstract":"Real-time and 3-D monitoring of cavitation activity is critical for safe, effective, and controlled treatments in cavitation-based focused ultrasound (FUS) therapies. This 3-D monitoring capability is essential for detecting off-target cavitation events, particularly in at-risk structures and those occurring outside the plane of 2-D imaging. In this work, we demonstrate that using row-column arrays (RCAs) for 3-D passive acoustic mapping (PAM), which can be easily integrated into commercial ultrasound scanners compared to using hemispherical arrays or matrix arrays, represents a potent solution. For that, we propose the RCA-PAM method for image formation. This method deploys the angular spectrum (AS) method to back-propagate 3-D harmonic wave fields using the passively received cavitation signals by the RCA’s row and column apertures, respectively. Then, the 3-D PAM volume is obtained by integrating the cross-spectrum of the two wave fields over a selected bandwidth. To further reduce image artifacts, we combine AS with dual-apodization with cross correlation (AS-DAX) for wave field propagation. Our experiments showed that RCA-PAM achieved 0.04±0.07 mm source localization error and comparable image quality to the ones reconstructed for the matrix array (same aperture size). We realized over 40 volumes/second reconstruction speed for a volume sized <inline-formula> <tex-math>$128,times , 128,times ,250$ </tex-math></inline-formula> voxels, using all frequency components in the RCA’s working bandwidth. We also demonstrate the seamless combination of RCA-PAM and B-mode imaging using the same RCA for 3-D monitoring of MB cavitation activity in a mouse tumor model. In summary, the use of RCAs for cavitation monitoring represents a promising avenue to minimize treatment risks in cavitation-based FUS therapies.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 9","pages":"1187-1198"},"PeriodicalIF":3.7,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553398","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}
Pub Date : 2025-07-01DOI: 10.1109/TUFFC.2025.3577872
{"title":"IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Publication Information","authors":"","doi":"10.1109/TUFFC.2025.3577872","DOIUrl":"https://doi.org/10.1109/TUFFC.2025.3577872","url":null,"abstract":"","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 7","pages":"C2-C2"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11061184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536376","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}
Pub Date : 2025-06-30DOI: 10.1109/TUFFC.2025.3584533
Arthur Floquet;Emmanuel Soubies;Duong-Hung Pham;Denis Kouame
The process of ultrasound (US) image formation can generally be modeled, using a linear and shift invariance approximation, as a convolution. In practice, the point spread function (PSF) is shift-variant. Here, we consider the restoration problem using a shift-variant PSF, where it is modeled as a product convolution. We argue that the US PSF varies smoothly enough for product convolution to serve as an efficient and effective direct model for US image restoration. We present a strategy for constructing the product-convolution operator and derive an efficient optimization scheme. We finally validate our approach on both simulated and real data, demonstrating state-of-the-art results while achieving significantly faster processing times.
{"title":"Spatially Variant Ultrasound Image Restoration With Product Convolution","authors":"Arthur Floquet;Emmanuel Soubies;Duong-Hung Pham;Denis Kouame","doi":"10.1109/TUFFC.2025.3584533","DOIUrl":"10.1109/TUFFC.2025.3584533","url":null,"abstract":"The process of ultrasound (US) image formation can generally be modeled, using a linear and shift invariance approximation, as a convolution. In practice, the point spread function (PSF) is shift-variant. Here, we consider the restoration problem using a shift-variant PSF, where it is modeled as a product convolution. We argue that the US PSF varies smoothly enough for product convolution to serve as an efficient and effective direct model for US image restoration. We present a strategy for constructing the product-convolution operator and derive an efficient optimization scheme. We finally validate our approach on both simulated and real data, demonstrating state-of-the-art results while achieving significantly faster processing times.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 9","pages":"1235-1244"},"PeriodicalIF":3.7,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144527728","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}
Use of ultrasound for coronary imaging in commercial echocardiography remains challenging because of the small nature of coronary vasculature and the myocardium’s intricate motion. Several super-resolution imaging techniques have been applied for coronary imaging; however, most of them only measure the coronary flow during the diastolic phase and have a long data acquisition time. To address these problems, this study proposes an adaptive frame selection approach for coronary vasculature imaging. In this approach, similar frames within cardiac cycles are selected using the sum of absolute difference (SAD) algorithm, and the coronary vasculature blood flow is calculated without using electrocardiographic (ECG) gating data. Experiments were performed in mouse hearts through high-frequency ultrafast ultrasound imaging. After similar frames were selected from several cardiac cycles (one-five cycles), a singular value decomposition (SVD) filter was applied to extract blood flow signals and obtain a dynamic coronary vasculature image, the accuracy of which was confirmed by measuring Doppler sonograms from the left coronary artery (LCA) and arterioles. The conventional method (without SAD), in which only blood flow in the diastolic phase is calculated, was also conducted to enable a comparison in terms of measured vessel size and signal-to-noise ratio (SNR). The SNR for the proposed approach was found to be $20.74~pm ~1.62$ dB, under the best parameter settings. The proposed approach was successfully verified in the small animal model and has potential for use in human dynamic coronary artery imaging.
{"title":"In Vivo Ultrasound Dynamic Coronary Blood Flow Imaging Through Adaptive Frame Selection Method","authors":"Deng-Yan Zhuang;Hsin Huang;Wei-Ting Chang;Chih-Chung Huang","doi":"10.1109/TUFFC.2025.3582154","DOIUrl":"10.1109/TUFFC.2025.3582154","url":null,"abstract":"Use of ultrasound for coronary imaging in commercial echocardiography remains challenging because of the small nature of coronary vasculature and the myocardium’s intricate motion. Several super-resolution imaging techniques have been applied for coronary imaging; however, most of them only measure the coronary flow during the diastolic phase and have a long data acquisition time. To address these problems, this study proposes an adaptive frame selection approach for coronary vasculature imaging. In this approach, similar frames within cardiac cycles are selected using the sum of absolute difference (SAD) algorithm, and the coronary vasculature blood flow is calculated without using electrocardiographic (ECG) gating data. Experiments were performed in mouse hearts through high-frequency ultrafast ultrasound imaging. After similar frames were selected from several cardiac cycles (one-five cycles), a singular value decomposition (SVD) filter was applied to extract blood flow signals and obtain a dynamic coronary vasculature image, the accuracy of which was confirmed by measuring Doppler sonograms from the left coronary artery (LCA) and arterioles. The conventional method (without SAD), in which only blood flow in the diastolic phase is calculated, was also conducted to enable a comparison in terms of measured vessel size and signal-to-noise ratio (SNR). The SNR for the proposed approach was found to be <inline-formula> <tex-math>$20.74~pm ~1.62$ </tex-math></inline-formula> dB, under the best parameter settings. The proposed approach was successfully verified in the small animal model and has potential for use in human dynamic coronary artery imaging.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 8","pages":"1108-1118"},"PeriodicalIF":3.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144496099","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}
Sparse arrays address the complexity of manufacturing large 2-D arrays. However, they usually suffer from a low signal-to-noise ratio (SNR) due to their small element size. The large divergent element (LDE) technology overcomes this limitation by simultaneously having a large emitting area and a large angular aperture. The aim of this work is to demonstrate the feasibility of imaging in B-mode using the LDE sparse array (LDESA), that is, increasing the sparse array SNR without noteworthy impact on contrast. This article provides the simulation, the design, and an experimental characterization of a 1-MHz LDESA. Simulations are performed using the angular impulse response-based ultrasound simulation (AIRUS), providing coupled image-transducer optimizations of LDESA designs. Probe parameters, including probe diameter, layout, LDE size, and electroacoustic response, are optimized to maximize the contrast ratio (CR). The final layout is a 100-mm-diameter Fermat spiral covered by 256 LDEs. Each LDE is 3.5 mm wide in diameter and experimentally reaches an angular aperture of 75° at −6 dB in echo. The transmit focused beam is 1° wide and steerable up to 60° with an amplitude loss of only 10 dB. The array exhibits a 2.2-mm lateral resolution and a 1.8-mm axial resolution in a wire experiment.
{"title":"Simulation, Design, and Characterization of a Large Divergent Element Sparse Array (LDESA) for 3-D Ultrasound Imaging","authors":"Jean-Baptiste Jacquet;Jean-Luc Guey;Pierre Kauffmann;Mohamed Tamraoui;Emmanuel Roux;Barbara Nicolas;Etienne Coffy;Hervé Liebgott","doi":"10.1109/TUFFC.2025.3583178","DOIUrl":"10.1109/TUFFC.2025.3583178","url":null,"abstract":"Sparse arrays address the complexity of manufacturing large 2-D arrays. However, they usually suffer from a low signal-to-noise ratio (SNR) due to their small element size. The large divergent element (LDE) technology overcomes this limitation by simultaneously having a large emitting area and a large angular aperture. The aim of this work is to demonstrate the feasibility of imaging in B-mode using the LDE sparse array (LDESA), that is, increasing the sparse array SNR without noteworthy impact on contrast. This article provides the simulation, the design, and an experimental characterization of a 1-MHz LDESA. Simulations are performed using the angular impulse response-based ultrasound simulation (AIRUS), providing coupled image-transducer optimizations of LDESA designs. Probe parameters, including probe diameter, layout, LDE size, and electroacoustic response, are optimized to maximize the contrast ratio (CR). The final layout is a 100-mm-diameter Fermat spiral covered by 256 LDEs. Each LDE is 3.5 mm wide in diameter and experimentally reaches an angular aperture of 75° at −6 dB in echo. The transmit focused beam is 1° wide and steerable up to 60° with an amplitude loss of only 10 dB. The array exhibits a 2.2-mm lateral resolution and a 1.8-mm axial resolution in a wire experiment.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 8","pages":"1041-1052"},"PeriodicalIF":3.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144496100","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}
Pub Date : 2025-06-24DOI: 10.1109/TUFFC.2025.3582773
Hassan Nahas;Billy Y. S. Yiu;Adrian J. Y. Chee;Takuro Ishii;Alfred C. H. Yu
Recent innovations in vector flow imaging promise to bring the modality closer to clinical application and allow for more comprehensive, high frame-rate vascular assessments. One such innovation is plane-wave multi-angle vector Doppler, where pulsed Doppler principles from multiple steering angles are used to realize vector flow imaging at frame rates upward of 1000 frames per second (fps). Currently, vector Doppler is limited by the presence of aliasing artifacts that have prevented its reliable realization at the bedside. In this work, we present a new aliasing-resistant vector Doppler imaging system that can be deployed at the bedside using a programmable ultrasound core, graphics processing unit (GPU) processing, and deep-learning principles. The framework supports two operational modes: 1) live imaging at 17 fps, where vector flow imaging serves to guide image view navigation in blood vessels with complex dynamics, and 2) on-demand replay mode, where flow data acquired at high frame rates of over 1000 fps is depicted as a slow-motion playback at 60 fps using an aliasing-resistant vector projectile visualization. Using with our new system, aliasing-free vector flow cineloops were successfully obtained in a stenosis phantom experiment and in human bifurcation imaging scans. This system represents a major engineering advance toward the clinical adoption of vector flow imaging.
{"title":"Bedside Ultrasound Vector Doppler Imaging System With GPU Processing and Deep Learning","authors":"Hassan Nahas;Billy Y. S. Yiu;Adrian J. Y. Chee;Takuro Ishii;Alfred C. H. Yu","doi":"10.1109/TUFFC.2025.3582773","DOIUrl":"10.1109/TUFFC.2025.3582773","url":null,"abstract":"Recent innovations in vector flow imaging promise to bring the modality closer to clinical application and allow for more comprehensive, high frame-rate vascular assessments. One such innovation is plane-wave multi-angle vector Doppler, where pulsed Doppler principles from multiple steering angles are used to realize vector flow imaging at frame rates upward of 1000 frames per second (fps). Currently, vector Doppler is limited by the presence of aliasing artifacts that have prevented its reliable realization at the bedside. In this work, we present a new aliasing-resistant vector Doppler imaging system that can be deployed at the bedside using a programmable ultrasound core, graphics processing unit (GPU) processing, and deep-learning principles. The framework supports two operational modes: 1) live imaging at 17 fps, where vector flow imaging serves to guide image view navigation in blood vessels with complex dynamics, and 2) on-demand replay mode, where flow data acquired at high frame rates of over 1000 fps is depicted as a slow-motion playback at 60 fps using an aliasing-resistant vector projectile visualization. Using with our new system, aliasing-free vector flow cineloops were successfully obtained in a stenosis phantom experiment and in human bifurcation imaging scans. This system represents a major engineering advance toward the clinical adoption of vector flow imaging.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"72 8","pages":"1079-1094"},"PeriodicalIF":3.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11049011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484163","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}
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