Pub Date : 2026-01-12DOI: 10.1109/OJUFFC.2026.3652600
Felix CORDES;Julia Scholtyssek;Karl-Ludwig Krieger
Carbon fibre reinforced composites are being used in more and more areas of application, for example in hydrogen storage tanks. In addition to structural-mechanical advantages, these materials also have disadvantages, such as susceptibility to mechanical damage. This makes structural monitoring advisable in safety-critical applications. In addition to the detection of damage, the localization of the source of the acoustic signal, respectively the damage, is a central component. Signal localization on fibre composites is a major challenge, due to the high direction dependency of the speed of acoustic signals. Measurement inaccuracies and low signal strengths, especially in noisy environments, lead to high localization errors when locating the source based on the difference in signal arrival times in a sensor network. When using triangulation-based methods, it is even possible that several plausible signal sources are identified. This article therefore analyses the extent to which localization accuracy is affected by a reduction in the signal-to-noise ratio. Two different localization methods are used for the investigations and their accuracy is evaluated when the signal-to-noise ratio is reduced. These are, on the one hand, classic triangulation, adapted to an anisotropic material. On the other hand, localization via a convolutional neural network is investigated. For the investigations, acoustic signals with different signal-to-noise ratios are applied to a carbon fibre prepreg plate in three series of measurements and localized using a sensor grid. In addition to the effect of the signal-to-noise ratio, the effect of the source position relative to the sensor grid is investigated.
{"title":"Comparison of Triangulation and CNN-Based Acoustic Source Localization on Carbon Fibre Reinforced Composites Considering the Signal-to-Noise Ratio","authors":"Felix CORDES;Julia Scholtyssek;Karl-Ludwig Krieger","doi":"10.1109/OJUFFC.2026.3652600","DOIUrl":"https://doi.org/10.1109/OJUFFC.2026.3652600","url":null,"abstract":"Carbon fibre reinforced composites are being used in more and more areas of application, for example in hydrogen storage tanks. In addition to structural-mechanical advantages, these materials also have disadvantages, such as susceptibility to mechanical damage. This makes structural monitoring advisable in safety-critical applications. In addition to the detection of damage, the localization of the source of the acoustic signal, respectively the damage, is a central component. Signal localization on fibre composites is a major challenge, due to the high direction dependency of the speed of acoustic signals. Measurement inaccuracies and low signal strengths, especially in noisy environments, lead to high localization errors when locating the source based on the difference in signal arrival times in a sensor network. When using triangulation-based methods, it is even possible that several plausible signal sources are identified. This article therefore analyses the extent to which localization accuracy is affected by a reduction in the signal-to-noise ratio. Two different localization methods are used for the investigations and their accuracy is evaluated when the signal-to-noise ratio is reduced. These are, on the one hand, classic triangulation, adapted to an anisotropic material. On the other hand, localization via a convolutional neural network is investigated. For the investigations, acoustic signals with different signal-to-noise ratios are applied to a carbon fibre prepreg plate in three series of measurements and localized using a sensor grid. In addition to the effect of the signal-to-noise ratio, the effect of the source position relative to the sensor grid is investigated.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"292-300"},"PeriodicalIF":2.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11345239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1109/OJUFFC.2025.3641005
Andrea Pulido;Nitin Burman;Sandro Queirós;Jan D’Hooge
Cardiac ultrasound deformation imaging is a non-invasive and widely used modality for assessing left ventricular function. However, due to the variable image quality observed in clinical routine, deformation estimation remains challenging. Recently, deep learning (DL) approaches have been proposed to estimate motion from ultrasound images. In this study, we investigated whether combining in vivo data with a synthetic dataset during training improves motion estimation accuracy while also benchmarking the DL-based estimates against a state-of-the-art traditional optical flow method. Results demonstrate that the deep learning-based method excels in tracking the dense motion fields on a frame-by-frame basis. However, when performing contour tracking, it results in lower end-systolic peak strain values compared to the traditional optical flow method.
{"title":"Impact of Training Data Composition on Deep Learning-Based Cardiac Motion Estimation","authors":"Andrea Pulido;Nitin Burman;Sandro Queirós;Jan D’Hooge","doi":"10.1109/OJUFFC.2025.3641005","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3641005","url":null,"abstract":"Cardiac ultrasound deformation imaging is a non-invasive and widely used modality for assessing left ventricular function. However, due to the variable image quality observed in clinical routine, deformation estimation remains challenging. Recently, deep learning (DL) approaches have been proposed to estimate motion from ultrasound images. In this study, we investigated whether combining in vivo data with a synthetic dataset during training improves motion estimation accuracy while also benchmarking the DL-based estimates against a state-of-the-art traditional optical flow method. Results demonstrate that the deep learning-based method excels in tracking the dense motion fields on a frame-by-frame basis. However, when performing contour tracking, it results in lower end-systolic peak strain values compared to the traditional optical flow method.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"286-291"},"PeriodicalIF":2.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1109/OJUFFC.2025.3639374
Joosje M. K. De Bakker;Ingvild K. Ekroll;Anne E. C. M. Saris;Jørgen Avdal
Velocity vector imaging (VVI) can suffer from poor signal-to-noise (SNR) conditions, eventually restricting the estimation of velocities at low SNRs. Cascaded dual-polarity wave (CDW) imaging has been shown to enhance blood-SNR, thereby improving cross-correlation-based VVI. However, the CDW decoding process is sensitive to motion, where imperfect summation and cancellation of pulses can lead to reduced amplitude gain and ghost pulses outside the main pulse. Multi/dual-angle transmits, combined with either autocorrelation- or cross-correlation-based axial velocity estimation, are commonly used for VVI. Both techniques have intrinsic limitations, such as speckle decorrelation and aliasing, and strengths, where autocorrelation is known to be more resistant to noise and cross-correlation results in more accurate estimates in high SNR conditions. This study evaluates the benefits of CDW imaging for both autocorrelation- and cross-correlation-based VVI using the FLUST simulation toolbox and experiments, including parabolic and rotational flow scenarios. The results indicate that autocorrelation performs consistently across the entire SNR range, while cross-correlation is more accurate and precise in high SNR conditions. CDW improves estimation performance in low SNR conditions, particularly for estimation of low velocities, with a more substantial performance boost for cross-correlation compared to autocorrelation. In general, CDW imaging shows to be beneficial for VVI, independent of the used velocity estimator.
{"title":"The Added Value of Cascaded Plane Wave Imaging for Autocorrelation- and Cross-Correlation-Based Velocity Vector Imaging","authors":"Joosje M. K. De Bakker;Ingvild K. Ekroll;Anne E. C. M. Saris;Jørgen Avdal","doi":"10.1109/OJUFFC.2025.3639374","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3639374","url":null,"abstract":"Velocity vector imaging (VVI) can suffer from poor signal-to-noise (SNR) conditions, eventually restricting the estimation of velocities at low SNRs. Cascaded dual-polarity wave (CDW) imaging has been shown to enhance blood-SNR, thereby improving cross-correlation-based VVI. However, the CDW decoding process is sensitive to motion, where imperfect summation and cancellation of pulses can lead to reduced amplitude gain and ghost pulses outside the main pulse. Multi/dual-angle transmits, combined with either autocorrelation- or cross-correlation-based axial velocity estimation, are commonly used for VVI. Both techniques have intrinsic limitations, such as speckle decorrelation and aliasing, and strengths, where autocorrelation is known to be more resistant to noise and cross-correlation results in more accurate estimates in high SNR conditions. This study evaluates the benefits of CDW imaging for both autocorrelation- and cross-correlation-based VVI using the FLUST simulation toolbox and experiments, including parabolic and rotational flow scenarios. The results indicate that autocorrelation performs consistently across the entire SNR range, while cross-correlation is more accurate and precise in high SNR conditions. CDW improves estimation performance in low SNR conditions, particularly for estimation of low velocities, with a more substantial performance boost for cross-correlation compared to autocorrelation. In general, CDW imaging shows to be beneficial for VVI, independent of the used velocity estimator.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"281-285"},"PeriodicalIF":2.9,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11272879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The simultaneous measurement of blood pressure (P) and volume flow rate (Q) is essential for a comprehensive hemodynamic assessment, yet it remains a significant technical challenge. This work presents a novel ultrasound-based system that enables the simultaneous estimation of high-resolution P and Q waveforms at the same vascular location using a single transducer. We propose a system that leverages ultrafast multi-angle plane wave imaging to acquire high-frame-rate B-mode image sequences. A machine learning optical flow model called RAFT was adapted and fine-tuned for ultrasound to perform robust vector flow imaging for Q quantification. Concurrently, an efficient 2-D speckle tracking algorithm tracks vessel wall motion to derive the diameter waveform, from which P is estimated using a calibrated exponential model. The method was evaluated in flow phantom experiments and in vivo on the carotid arteries of healthy subjects. In phantom studies, the proposed method demonstrated high accuracy, with pressure estimates achieving a root-mean-square error of 1.76 mmHg against reference sensors. Crucially, Q estimates showed improved accuracy compared to conventional color Doppler and existing vector flow imaging methods such as blood speckle tracking and multi-angle vector Doppler. In vivo results confirmed that the proposed method provides high-resolution P and Q waveforms, enabling the reliable calculation of hemodynamic energy parameters sensitive to vascular aging. This work introduces a fully ML-driven ultrasound velocimetry method integrated with blood pressure estimation from vessel wall motion, potentially enhancing the diagnosis of cardiovascular and cerebrovascular diseases.
{"title":"Simultaneous Estimation of Blood Pressure and Volume Flow Using Deep Learning- Enhanced Ultrafast Ultrasound","authors":"Ching-Yao Lu;Shao-Kai Lu;Hsiang-Chung Cheng;Yun-Chieh Chou;Jiun-Jr Wang;Shao-Yuan Chuang;Yin-Chi Wu;Chen-Hua Lin;Chi-Jung Huang;Bao-Yu Hsieh;Hao-Min Cheng;Geng-Shi Jeng","doi":"10.1109/OJUFFC.2025.3639212","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3639212","url":null,"abstract":"The simultaneous measurement of blood pressure (P) and volume flow rate (Q) is essential for a comprehensive hemodynamic assessment, yet it remains a significant technical challenge. This work presents a novel ultrasound-based system that enables the simultaneous estimation of high-resolution P and Q waveforms at the same vascular location using a single transducer. We propose a system that leverages ultrafast multi-angle plane wave imaging to acquire high-frame-rate B-mode image sequences. A machine learning optical flow model called RAFT was adapted and fine-tuned for ultrasound to perform robust vector flow imaging for Q quantification. Concurrently, an efficient 2-D speckle tracking algorithm tracks vessel wall motion to derive the diameter waveform, from which P is estimated using a calibrated exponential model. The method was evaluated in flow phantom experiments and in vivo on the carotid arteries of healthy subjects. In phantom studies, the proposed method demonstrated high accuracy, with pressure estimates achieving a root-mean-square error of 1.76 mmHg against reference sensors. Crucially, Q estimates showed improved accuracy compared to conventional color Doppler and existing vector flow imaging methods such as blood speckle tracking and multi-angle vector Doppler. In vivo results confirmed that the proposed method provides high-resolution P and Q waveforms, enabling the reliable calculation of hemodynamic energy parameters sensitive to vascular aging. This work introduces a fully ML-driven ultrasound velocimetry method integrated with blood pressure estimation from vessel wall motion, potentially enhancing the diagnosis of cardiovascular and cerebrovascular diseases.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"228-241"},"PeriodicalIF":2.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271676","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-25DOI: 10.1109/OJUFFC.2025.3636834
Julian Kober;Tönnis Trittler;Edgar M. G. Dorausch;Cornelius Kühnöl;Julius Weber;Marc Hauer;Martin Oppermann;Henning Heuer;Jochen Hampe;Richard Nauber;Moritz Herzog
Emerging ultrasound imaging technologies such as wearables and miniaturized invasive devices require exceptional piezoelectric performance alongside flexibility, small form factors, biocompatibility and scalable production capabilities. To address this, we investigate the embedding of high-performance lead magnesium niobate-lead titanate (PMN-PT) transducers in a flexible and biocompatible Liquid Crystal Polymer (LCP) substrate with integrated conductor tracks. This approach aims to improve mechanical reliability and enable industrial-scale production of compact ultrasound devices. The piezoelectric elements were contacted during the embedding process, involving exposure to heat and pressure, requiring a subsequent repolarization process to restore the piezoelectric behavior. Performance was validated against encapsulated wire-bonded reference samples through electrical impedance measurements and acoustic pitch-catch experiments using a hydrophone in a water tank, with different sound incidence angles. After repoling, the embedded single crystal transducer demonstrated expected piezoelectric behavior in impedance data and achieved a peak negative output pressure amplitude of 4.70 kPa (measured at 10 mm distance in water), compared to 4.45 kPa for the encapsulated wire-bonded reference sample, representing a difference of $approx ~5$ %. Directivity patterns showed minimal differences in emission angle, with resonance frequencies varying between prototypes due to the inherent characteristics of different manufacturing approaches in the acoustic stack. This embedding approach shows promising results for miniaturized applications, including external ultrasound wearables and patches, as well as invasive devices such as intravascular and implantable ultrasound systems.
{"title":"Miniaturized Ultrasonic Transducer With PMN-PT Embedded Into Flexible LCP Substrate for Biocompatible Applications","authors":"Julian Kober;Tönnis Trittler;Edgar M. G. Dorausch;Cornelius Kühnöl;Julius Weber;Marc Hauer;Martin Oppermann;Henning Heuer;Jochen Hampe;Richard Nauber;Moritz Herzog","doi":"10.1109/OJUFFC.2025.3636834","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3636834","url":null,"abstract":"Emerging ultrasound imaging technologies such as wearables and miniaturized invasive devices require exceptional piezoelectric performance alongside flexibility, small form factors, biocompatibility and scalable production capabilities. To address this, we investigate the embedding of high-performance lead magnesium niobate-lead titanate (PMN-PT) transducers in a flexible and biocompatible Liquid Crystal Polymer (LCP) substrate with integrated conductor tracks. This approach aims to improve mechanical reliability and enable industrial-scale production of compact ultrasound devices. The piezoelectric elements were contacted during the embedding process, involving exposure to heat and pressure, requiring a subsequent repolarization process to restore the piezoelectric behavior. Performance was validated against encapsulated wire-bonded reference samples through electrical impedance measurements and acoustic pitch-catch experiments using a hydrophone in a water tank, with different sound incidence angles. After repoling, the embedded single crystal transducer demonstrated expected piezoelectric behavior in impedance data and achieved a peak negative output pressure amplitude of 4.70 kPa (measured at 10 mm distance in water), compared to 4.45 kPa for the encapsulated wire-bonded reference sample, representing a difference of <inline-formula> <tex-math>$approx ~5$ </tex-math></inline-formula> %. Directivity patterns showed minimal differences in emission angle, with resonance frequencies varying between prototypes due to the inherent characteristics of different manufacturing approaches in the acoustic stack. This embedding approach shows promising results for miniaturized applications, including external ultrasound wearables and patches, as well as invasive devices such as intravascular and implantable ultrasound systems.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"269-275"},"PeriodicalIF":2.9,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11268466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-25DOI: 10.1109/OJUFFC.2025.3636108
Beatrice Federici;Ruud J. G. Van Sloun;Massimo Mischi
This work introduces a closed-loop transmit beamsteering system for fetal Doppler ultrasound, driven by an active inference agent. The agent actively reduces uncertainty in fetal heart localization - estimated from power Doppler data via sequential Monte Carlo methods - by adaptively steering the ultrasound beam. This uncertainty-aware approach maintains high-quality Doppler signals and enables robust heart rate tracking, even under challenging, low signal-to-noise conditions.
{"title":"Active Inference for Closed-Loop Transmit Beamsteering in Fetal Doppler Ultrasound","authors":"Beatrice Federici;Ruud J. G. Van Sloun;Massimo Mischi","doi":"10.1109/OJUFFC.2025.3636108","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3636108","url":null,"abstract":"This work introduces a closed-loop transmit beamsteering system for fetal Doppler ultrasound, driven by an active inference agent. The agent actively reduces uncertainty in fetal heart localization - estimated from power Doppler data via sequential Monte Carlo methods - by adaptively steering the ultrasound beam. This uncertainty-aware approach maintains high-quality Doppler signals and enables robust heart rate tracking, even under challenging, low signal-to-noise conditions.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"276-280"},"PeriodicalIF":2.9,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11269010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-20DOI: 10.1109/OJUFFC.2025.3635126
D. S. Bidouba Sanvany;F. Kosior;D. Beyssen;A. Gigodot;E. Gaudion;F. Sarry
Our study aims to investigate the impact of SAW on biological cells, including adherent (SaOs-2 osteoblasts) and circulating (THP-1 monocytes) cells, to assess the physical stresses on the latter, specifically acoustic radiation pressure and shear stresses, which are crucial in cell stimulation within biomedicine. We have presented the simulation for extracting shear stresses from circulating and adherent cells at resonant frequencies of 20 and 40 MHz, respectively. We utilized the direct simulation method to enhance liquid-level optimization. No one has previously presented this approach. Our model underwent validation by comparing simulation results with those obtained from the experiment, including wave amplitude, particle velocity temperature, and streaming shape. After validating the simulation model, we determined the shear stresses on the particles. An optimization study showed that the optimal level for adherent cells is 5 mm, whereas for circulating cells, it is 7 mm. We have also demonstrated that the heating is significantly above 20 dBm. The heating exceeds 1°C, which is harmful to biological cells.
{"title":"Exploring Fluid Dynamics to Analyze Cellular Stress Induced by Surface Acoustic Waves in Biological Applications","authors":"D. S. Bidouba Sanvany;F. Kosior;D. Beyssen;A. Gigodot;E. Gaudion;F. Sarry","doi":"10.1109/OJUFFC.2025.3635126","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3635126","url":null,"abstract":"Our study aims to investigate the impact of SAW on biological cells, including adherent (SaOs-2 osteoblasts) and circulating (THP-1 monocytes) cells, to assess the physical stresses on the latter, specifically acoustic radiation pressure and shear stresses, which are crucial in cell stimulation within biomedicine. We have presented the simulation for extracting shear stresses from circulating and adherent cells at resonant frequencies of 20 and 40 MHz, respectively. We utilized the direct simulation method to enhance liquid-level optimization. No one has previously presented this approach. Our model underwent validation by comparing simulation results with those obtained from the experiment, including wave amplitude, particle velocity temperature, and streaming shape. After validating the simulation model, we determined the shear stresses on the particles. An optimization study showed that the optimal level for adherent cells is 5 mm, whereas for circulating cells, it is 7 mm. We have also demonstrated that the heating is significantly above 20 dBm. The heating exceeds 1°C, which is harmful to biological cells.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"254-268"},"PeriodicalIF":2.9,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11261883","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1109/OJUFFC.2025.3631426
Anna V. Phillips;Cherie M. Kuzmiak;Doreen Steed;Caterina M. Gallippi
Viscoelastic response (VisR) ultrasound has been developed by our group to interrogate tissue stiffness and viscosity. VisR has several potential advantages for breast cancer diagnostic imaging such being non-invasive and low-cost. Because ultrasound can penetrate dense breasts more effectively than mammograms, it may improve the detection of malignant masses in women with dense breasts. VisR-based estimates of stiffness, viscosity, and anisotropy have been shown in our preliminary studies to discriminate malignant and benign breast lesions. However, a potential limitation of VisR could be dependence on tissue pre-loading from applied surface compression by the practitioner. We conducted an IRB-approved clinical study of 20 women with no known breast pathologies to assess the impact of compression on VisR measurements of peak displacement (PD), relative elasticity (RE), relative viscosity (RV), and degree of anisotropy (DoA). Participants were between the ages of 30-90, and 10/20 had mammographically dense breasts. We found that surface compression significantly affected measurements of PD, RE, and RV in breast tissue, in vivo. In particular, in women with dense breasts, stiffness (via PD and RE) increased significantly with applied compression. DoA of PD, RE, and RV increased, decreased, or stayed the same with compression. No significant difference was found in DoA with compression between the breast density groups. Based on these findings, we recommend that surface compression be standardized and monitored when using VisR for clinical breast imaging, especially in women with dense breasts. Further studies are needed to identify an optimal strain range for VisR measurement repeatability.
{"title":"Surface Compression Alters in Vivo VisR Stiffness, Viscosity, and Anisotropy Measurements in Human Breast","authors":"Anna V. Phillips;Cherie M. Kuzmiak;Doreen Steed;Caterina M. Gallippi","doi":"10.1109/OJUFFC.2025.3631426","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3631426","url":null,"abstract":"Viscoelastic response (VisR) ultrasound has been developed by our group to interrogate tissue stiffness and viscosity. VisR has several potential advantages for breast cancer diagnostic imaging such being non-invasive and low-cost. Because ultrasound can penetrate dense breasts more effectively than mammograms, it may improve the detection of malignant masses in women with dense breasts. VisR-based estimates of stiffness, viscosity, and anisotropy have been shown in our preliminary studies to discriminate malignant and benign breast lesions. However, a potential limitation of VisR could be dependence on tissue pre-loading from applied surface compression by the practitioner. We conducted an IRB-approved clinical study of 20 women with no known breast pathologies to assess the impact of compression on VisR measurements of peak displacement (PD), relative elasticity (RE), relative viscosity (RV), and degree of anisotropy (DoA). Participants were between the ages of 30-90, and 10/20 had mammographically dense breasts. We found that surface compression significantly affected measurements of PD, RE, and RV in breast tissue, in vivo. In particular, in women with dense breasts, stiffness (via PD and RE) increased significantly with applied compression. DoA of PD, RE, and RV increased, decreased, or stayed the same with compression. No significant difference was found in DoA with compression between the breast density groups. Based on these findings, we recommend that surface compression be standardized and monitored when using VisR for clinical breast imaging, especially in women with dense breasts. Further studies are needed to identify an optimal strain range for VisR measurement repeatability.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"242-253"},"PeriodicalIF":2.9,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11240139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-07DOI: 10.1109/OJUFFC.2025.3630590
Lorenzo Capineri
The design of electronic systems for ultrasonic guided wave structural health monitoring requires a dedicated electronic front-end considering the peculiarities of this application field. The characteristics of ultrasonic guided wave piezoelectric transducers are first decided based on the operating environment, the material of the structures and their dimensions, as well as the definition of connections and diagnostics of the transducers. Another specific feature of electronic design is for systems operating both in passive mode for impact detection and in active mode for damage detection and positioning. These two operating modes correspond to different analog electronic chains because the received signals have different amplitude levels and frequency spectrum. The paper will review the main building blocks of the electronic system with a focus on analog front-end electronic circuits and propose a new modular architecture for the electronics to address different SHM scenarios.
{"title":"Ultrasonic Guided Wave Transducers and Electronic System Design for Structural Health Monitoring","authors":"Lorenzo Capineri","doi":"10.1109/OJUFFC.2025.3630590","DOIUrl":"https://doi.org/10.1109/OJUFFC.2025.3630590","url":null,"abstract":"The design of electronic systems for ultrasonic guided wave structural health monitoring requires a dedicated electronic front-end considering the peculiarities of this application field. The characteristics of ultrasonic guided wave piezoelectric transducers are first decided based on the operating environment, the material of the structures and their dimensions, as well as the definition of connections and diagnostics of the transducers. Another specific feature of electronic design is for systems operating both in passive mode for impact detection and in active mode for damage detection and positioning. These two operating modes correspond to different analog electronic chains because the received signals have different amplitude levels and frequency spectrum. The paper will review the main building blocks of the electronic system with a focus on analog front-end electronic circuits and propose a new modular architecture for the electronics to address different SHM scenarios.","PeriodicalId":73301,"journal":{"name":"IEEE open journal of ultrasonics, ferroelectrics, and frequency control","volume":"5 ","pages":"214-227"},"PeriodicalIF":2.9,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11232463","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1109/OJUFFC.2025.3618637
Jeffrey A. Ketterling;Geraldi Wahyulaksana;Marisa S. Bazzi;Hadi Wiputra
Ultrasound simulations of blood flow are useful to evaluate or optimize new transmit schemes, transducer geometries, or post processing methods such as vector flow. In cases of complex flow, a flow domain model (FDM) is often used to define the time history of the velocity field. Scatterers representing blood cells are seeded in the flow field and their positions are updated each time step after spatial and temporal interpolation of the FDM velocity field. At each time step, the scatterers are passed to an ultrasound simulator to generate synthetic ultrasound backscatter data. Here, a technique is described to continuously track, without temporal discontinuities, a stable concentration of scatterers representing complex flow with reverse, rotational, out-of-plane and/or helical features. The unique aspects of the tracking approach are 1) refresh zones at the input and output flow ports that randomly reseed scatterers each time step, 2) a stagnation threshold to remove low velocity orphaned scatterers near the boundary of the flow field, and 3) continuous tracking of particles in the full flow volume. The method can be adapted to any FDM, ultrasound simulator, transducer, or transmission scheme. To demonstrate the overall pipeline, we use the results of a prior fluid structure interaction (FSI) model of a mouse aorta to generate a continuous high-speed, plane-wave ultrasound simulation over 4 cardiac cycles with a 15-MHz linear array. The data were processed to produce vector flow to validate that the ultrasound vector-flow field was consistent with the FSI velocity field.
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