Showing papers in "IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control in 2018"

Ultrasound Localization Microscopy and Super-Resolution: A State of the Art

Abstract: Because it drives the compromise between resolution and penetration, the diffraction limit has long represented an unreachable summit to conquer in ultrasound imaging. Within a few years after the introduction of optical localization microscopy, we proposed its acoustic alter ego that exploits the micrometric localization of microbubble contrast agents to reconstruct the finest vessels in the body in-depth. Various groups now working on the subject are optimizing the localization precision, microbubble separation, acquisition time, tracking, and velocimetry to improve the capacity of ultrasound localization microscopy (ULM) to detect and distinguish vessels much smaller than the wavelength. It has since been used in vivo in the brain, the kidney, and tumors. In the clinic, ULM is bound to improve drastically our vision of the microvasculature, which could revolutionize the diagnosis of cancer, arteriosclerosis, stroke, and diabetes.

Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

Abstract: Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This paper aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane-wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high-frame-rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this paper, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation, and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-sectional profile with full-width at half-maximum of $57~\mu \text{m}$ could be imaged at approximately 2-cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution $\sim 200~\mu \text{m}$ ). Cortical microvessels that are $76~\mu \text{m}$ apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

Ultrasound Open Platforms for Next-Generation Imaging Technique Development

Abstract: Open platform (OP) ultrasound systems are aimed primarily at the research community. They have been at the forefront of the development of synthetic aperture, plane wave, shear wave elastography, and vector flow imaging. Such platforms are driven by a need for broad flexibility of parameters that are normally preset or fixed within clinical scanners. OP ultrasound scanners are defined to have three key features including customization of the transmit waveform, access to the prebeamformed receive data, and the ability to implement real-time imaging. In this paper, a formative discussion is given on the development of OPs from both the research community and the commercial sector. Both software- and hardware-based architectures are considered, and their specifications are compared in terms of resources and programmability. Software-based platforms capable of real-time beamforming generally make use of scalable graphics processing unit architectures, whereas a common feature of hardware-based platforms is the use of field-programmable gate array and digital signal processor devices to provide additional on-board processing capacity. OPs with extended number of channels (>256) are also discussed in relation to their role in supporting 3-D imaging technique development. With the increasing maturity of OP ultrasound scanners, the pace of advancement in ultrasound imaging algorithms is poised to be accelerated.

Ultraino: An Open Phased-Array System for Narrowband Airborne Ultrasound Transmission

Abstract: Modern ultrasonic phased-array controllers are electronic systems capable of delaying the transmitted or received signals of multiple transducers. Configurable transmit–receive array systems, capable of electronic steering and shaping of the beam in near real-time, are available commercially, for example, for medical imaging. However, emerging applications, such as ultrasonic haptics, parametric audio, or ultrasonic levitation, require only a small subset of the capabilities provided by the existing controllers. To meet this need, we present Ultraino, a modular, inexpensive, and open platform that provides hardware, software, and example applications specifically aimed at controlling the transmission of narrowband airborne ultrasound. Our system is composed of software, driver boards, and arrays that enable users to quickly and efficiently perform research in various emerging applications. The software can be used to define array geometries, simulate the acoustic field in real time, and control the connected driver boards. The driver board design is based on an Arduino Mega and can control 64 channels with a square wave of up to 17 Vpp and $\pi $ /5 phase resolution. Multiple boards can be chained together to increase the number of channels. The 40-kHz arrays with flat and spherical geometries are demonstrated for parametric audio generation, acoustic levitation, and haptic feedback.

Two-Stage Motion Correction for Super-Resolution Ultrasound Imaging in Human Lower Limb

Abstract: The structure of microvasculature cannot be resolved using conventional ultrasound (US) imaging due to the fundamental diffraction limit at clinical US frequencies. It is possible to overcome this resolution limitation by localizing individual microbubbles through multiple frames and forming a superresolved image, which usually requires seconds to minutes of acquisition. Over this time interval, motion is inevitable and tissue movement is typically a combination of large- and small-scale tissue translation and deformation. Therefore, super-resolution (SR) imaging is prone to motion artifacts as other imaging modalities based on multiple acquisitions are. This paper investigates the feasibility of a two-stage motion estimation method, which is a combination of affine and nonrigid estimation, for SR US imaging. First, the motion correction accuracy of the proposed method is evaluated using simulations with increasing complexity of motion. A mean absolute error of 12.2 $\mu \text{m}$ was achieved in simulations for the worst-case scenario. The motion correction algorithm was then applied to a clinical data set to demonstrate its potential to enable in vivo SR US imaging in the presence of patient motion. The size of the identified microvessels from the clinical SR images was measured to assess the feasibility of the two-stage motion correction method, which reduced the width of the motion-blurred microvessels to approximately 1.5-fold.

SUSHI: Sparsity-Based Ultrasound Super-Resolution Hemodynamic Imaging

Abstract: Identifying and visualizing vasculature within organs and tumors has major implications in managing cardiovascular diseases and cancer. Contrast-enhanced ultrasound scans detect slow-flowing blood, facilitating noninvasive perfusion measurements. However, their limited spatial resolution prevents the depiction of microvascular structures. Recently, super-localization ultrasonography techniques have surpassed this limit. However, they require long acquisition times of several minutes, preventing the detection of hemodynamic changes. We present a fast super-resolution method that exploits sparsity in the underlying vasculature and statistical independence within the measured signals. Similar to super-localization techniques, this approach improves the spatial resolution by up to an order of magnitude compared to standard scans. Unlike super-localization methods, it requires acquisition times of only tens of milliseconds. We demonstrate a temporal resolution of ~25 Hz, which may enable functional super-resolution imaging deep within the tissue, surpassing the temporal resolution limitations of current super-resolution methods, e.g., in neural imaging. The subsecond acquisitions make our approach robust to motion artifacts, simplifying in vivo use of super-resolution ultrasound.

Sparse Convolutional Beamforming for Ultrasound Imaging

Abstract: The standard technique used by commercial medical ultrasound systems to form B-mode images is delay and sum (DAS) beamforming. However, DAS often results in limited image resolution and contrast that are governed by the center frequency and the aperture size of the ultrasound transducer. A large number of elements lead to improved resolution but at the same time increase the data size and the system cost due to the receive electronics required for each element. Therefore, reducing the number of receiving channels while producing high-quality images is of great importance. In this paper, we introduce a nonlinear beamformer called COnvolutional Beamforming Algorithm (COBA), which achieves significant improvement of lateral resolution and contrast. In addition, it can be implemented efficiently using the fast Fourier transform. Based on the COBA concept, we next present two sparse beamformers with closed-form expressions for the sensor locations, which result in the same beam pattern as DAS and COBA while using far fewer array elements. Optimization of the number of elements shows that they require a minimal number of elements that are on the order of the square root of the number used by DAS. The performance of the proposed methods is tested and validated using simulated data, phantom scans, and in vivo cardiac data. The results demonstrate that COBA outperforms DAS in terms of resolution and contrast and that the suggested beamformers offer a sizable element reduction while generating images with an equivalent or improved quality in comparison with DAS.

Regularized Spectral Log Difference Technique for Ultrasonic Attenuation Imaging

Abstract: The attenuation coefficient slope (ACS) has the potential to be used for tissue characterization and as a diagnostic ultrasound tool, hence complementing B-mode images. The ACS can be valuable for the estimation of other ultrasound parameters such as the backscatter coefficient. There is a well-known tradeoff between the precision of the estimated ACS values and the data block size used in the spectral-based techniques such as the spectral-log difference (SLD). This tradeoff limits the practical usefulness of the spectral-based attenuation imaging techniques. In this paper, the regularized SLD (RSLD) technique is presented in detail, and evaluated with simulations and experiments with physical phantoms, ex vivo and in vivo . The RSLD technique allowed decreasing estimation variance when using small data block sizes, i.e., fivefold reduction in the standard deviation of percentage error when using data block sizes larger than $20\lambda \times 20\lambda $ and more than a tenfold reduction when using $10\lambda \times 10\lambda $ data blocks. The precision improvement was obtained without sacrificing estimation accuracy (i.e., estimation bias improved in 70% of the cases by 10% of the ground truth-value on average while degraded in 30% of the cases by 3% of the ground truth-value on average). The improvements in precision allowed for better differentiation of inclusions especially when using small data blocks (i.e., smaller than $20\lambda \times 20\lambda $ ) where the contrast-to-noise ratio improved by an order of magnitude on average. The results suggest that the RSLD allows for the reconstruction of attenuation coefficient images with an improved tradeoff between spatial resolution and estimation precision.

A Spatial Coherence Approach to Minimum Variance Beamforming for Plane-Wave Compounding

Abstract: A new approach to implement minimum variance distortionless response (MVDR) beamforming is introduced for coherent plane-wave compounding (CPWC). MVDR requires the covariance matrix of the incoming signal to be estimated and a spatial smoothing approximation is usually adopted to prevent this calculation from being underconstrained. In the new approach, we analyze MVDR as a spatial filter that decorrelates signals received at individual channels before summation. Based on the analysis, we develop two MVDR beamformers without using any spatial smoothing. First, MVDR weights are applied to the received signals after accumulating the data over transmits at different angles, while the second involves weighting the data collected in individual transmits and compounding over the transducer elements. In both cases, the covariance matrix is estimated using a set of slightly different combinations of the echo data. We show the sufficient statistic for this estimation that can be described by approximating the correlation among the backscattered ultrasound signals to their spatial coherence. Using the van Cittert–Zernike theorem, their statistical similarity is assessed by relating the spatial coherence to the profile of the source intensity. Both spatial-coherence-based MVDR beamformers are evaluated on data sets acquired from simulation, phantom, and in vivo studies. Imaging results show that they offer improvements over simple coherent compounding in terms of spatial and contrast resolutions. They also outperform other existing MVDR-based methods in the literature that are applied to CPWC.

Recovery of the Complete Data Set From Focused Transmit Beams

Abstract: The focused transmit beam is a standard tool for clinical ultrasound scanning, concentrating energy from a number of array elements toward an imaging target. However, above and below the transmit focus, much of the energy in the beam is spread in a broadened main lobe and long off-axis tails that are ignored by conventional beamforming methods. This paper proposes a method to decompose a set of focused transmit beams into their constituent components—diverging waves from individual array elements. The recovery of this complete data set enables synthetic transmit focusing at all points in the field of view without beam shape or focal depth artifacts commonly associated with virtual source synthetic aperture beamforming. An efficient frequency-domain linear decoding implementation is introduced. The principles of the method are demonstrated both in transmit field simulations and experimental imaging. At depth, up to a 9.6-dB improvement in electronic signal-to-noise ratio and 8.9-dB improvement in contrast were observed in comparison with conventional dynamic receive beamforming. The proposed method is broadly applicable to existing scan sequences and requires only channel data for processing.

Phased Array Focusing for Acoustic Wireless Power Transfer

Abstract: Wireless power transfer (WPT) through acoustic waves can achieve higher efficiencies than inductive coupling when the distance is above several times the transducer size. This paper demonstrates the use of ultrasonic phased arrays to focus power to receivers at arbitrary locations to increase the power transfer efficiency. Using a phased array consisting of 37 elements at a distance nearly 5 times the receiver transducer diameter, a factor of 2.6 increase in efficiency was achieved when compared to a case equivalent to a single large transducer with the same peak efficiency distance. The array has a total diameter of 7 cm, and transmits through air at 40 kHz to a 1.1-cm diameter receiver, achieving a peak overall efficiency of 4% at a distance of 5 cm. By adjusting the focal distance, the efficiency can also be maintained relatively constant at distances up to 9 cm. Numerical models were developed and shown to closely match the experimental energy transfer behavior; modeling results indicate that the efficiency can be further doubled by increasing the number of elements. For comparison, an inductive WPT system was also built with the diameters of the transmitting and receiving coils equivalent to the dimensions of the transmitting ultrasonic phased array and receiver transducer, and the acoustic WPT system achieved higher efficiencies than the inductive WPT system when the transmit-to-receive distance is above 5 cm. In addition, beam angle steering was demonstrated by using a simplified seven-element 1-D array, achieving power transfer less dependent on receiver placement.

Lag-One Coherence as a Metric for Ultrasonic Image Quality

Abstract: Reliable assessment of image quality is an important but challenging task in complex imaging environments such as those encountered in vivo . To address this challenge, we propose a novel imaging metric, known as the lag-one coherence (LOC), which leverages the spatial coherence between nearest-neighbor array elements to provide a local measure of thermal and acoustic noise. In this paper, we derive the theory that relates LOC and the conventional image quality metrics of contrast and contrast-to-noise ratio (CNR) to channel noise. Simulation and phantom studies are performed to validate this theory and compare the variability of LOC to that of conventional metrics. We further evaluate the performance of LOC using matched measurements of contrast, CNR, and temporal correlation from in vivo liver images formed with varying mechanical index (MI) to assess the feasibility of adaptive acoustic output selection using LOC feedback. Simulation and phantom results reveal a lower variability in LOC relative to contrast and CNR over a wide range of clinically relevant noise levels. This improved stability is supported by in vivo measurements of LOC which show an increased monotonicity with changes in MI compared to matched measurements of contrast and CNR (88.6% and 85.7% of acquisitions, respectively). The sensitivity of LOC to stationary acoustic noise is evidenced by positive correlations between LOC and contrast ( $r=0.74$ ) and LOC and CNR ( $r=0.66$ ) at high acoustic output levels in the absence of thermal noise. Results indicate that LOC provides repeatable characterization of patient-specific trends in image quality, demonstrating feasibility in the selection of acoustic output using LOC and its application for in vivo image quality assessment.

Using the Deep Space Atomic Clock for Navigation and Science

Abstract: Routine use of one-way radiometric tracking for deep space navigation and radio science is not possible today because spacecraft frequency and time references that use state-of-the-art ultrastable oscillators introduce errors from their intrinsic drift and instability on timescales past 100 s. The Deep Space Atomic Clock (DSAC), currently under development as a NASA Technology Demonstration Mission, is an advanced prototype of a space-flight suitable, mercury-ion atomic clock that can provide an unprecedented frequency and time stability in a space-qualified clock. Indeed, the ground-based results of the DSAC space demonstration unit have already achieved an Allan deviation of $2 \times 10^{-15}$ at one day; space performance on this order will enable the use of one-way radiometric signals for deep space navigation and radio science.

High Spatial–Temporal Resolution Reconstruction of Plane-Wave Ultrasound Images With a Multichannel Multiscale Convolutional Neural Network

Abstract: In recent years, plane-wave imaging (PWI) has attracted considerable attention because of its high temporal resolution. However, the low spatial resolution of PWI limits its clinical applications, which has inspired various studies on the high spatial resolution reconstruction of PW ultrasound images. Although compounding methods and traditional high spatial resolution reconstruction approaches can improve the image quality, these techniques decrease the temporal resolution. Since learning methods can fully reserve the high temporal resolution of PW ultrasounds, a novel convolutional neural network (CNN) model for the high spatial–temporal resolution reconstruction of PW ultrasound images is proposed in this paper. Considering the multiangle form of PW data, a multichannel model is introduced to produce balanced training. To combine local and contextual information, the multiscale model is adopted. These two innovations constitute our multichannel and multiscale CNN (MMCNN) model. Compared with traditional CNN methods, the proposed model uses a two-stage structure in which a cascading wavelet postprocessing stage is combined with the trained MMCNN model. Cascading wavelet postprocessing aims to preserve speckle information. Furthermore, a feedback system is appended to the iteration process of the network training to solve the overfitting problem and help produce convergence. Based on these improvements, an end-to-end mapping is established between a single-angle B-mode PW image and its corresponding multiangle compounded, high-resolution image. The experiments were conducted on simulated, phantom, and real human data. The advantages of our proposed method were compared with a coherent PW compounding method, a conventional maximum a posteriori -based high spatial resolution reconstruction method, and a 2-D CNN compounding method, and the results verified that our approach is capable of attaining a better temporal resolution and comparable spatial resolution. In clinical usage, the proposed method is equipped to satisfy with many ultrafast imaging applications, which require high spatial–temporal resolution. i

Inverse Problem of Ultrasound Beamforming With Sparsity Constraints and Regularization

Abstract: Ultrasound (US) beamforming is the process of reconstructing an image from acquired echo traces on several transducer elements. Typical beamforming approaches, such as delay-and-sum, perform simple projection operations, while techniques using statistical information also exist, e.g., adaptive, phase coherence, delay-multiply-and-sum, and sparse coding approaches. Inspired by the feasibility and success of inverse problem (IP) formulations in several image reconstruction problems, such as computed tomography, we herein devise an IP approach for US beamforming. We define a linear forward model for the synthesis of the beamformed image, and solve its IP thanks to several intuitive and physics-based constraints and regularization terms proposed. These reflect the prior knowledge about the spectra of carrier signal and spatial coherence of modulated signal. These constraints admit effective formulation through sparse representations. Our proposed method was evaluated for plane-wave imaging (PWI) that transmits unfocused waves, enabling high frame rates with large field of view at the expense of much lower image quality with conventional beamforming techniques. Results are evaluated in numerical simulations, as well as tissue-mimicking phantoms and in vivo data provided by PWI challenge in medical US. The best results achieved by our proposed techniques are 0.39-mm full-width at half-maximum for spatial resolution and 16.3-dB contrast-to-noise ratio, using a single plane-wave transmit.

High-Frame-Rate Speckle-Tracking Echocardiography

Abstract: Conventional echocardiography is the leading modality for noninvasive cardiac imaging. It has been recently illustrated that high-frame-rate echocardiography using diverging waves could improve cardiac assessment. The spatial resolution and contrast associated with this method are commonly improved by coherent compounding of steered beams. However, owing to fast tissue velocities in the myocardium, the summation process of successive diverging waves can lead to destructive interferences if motion compensation (MoCo) is not considered. Coherent compounding methods based on MoCo have demonstrated their potential to provide high-contrast B-mode cardiac images. Ultrafast speckle-tracking echocardiography (STE) based on common speckle-tracking algorithms could substantially benefit from this original approach. In this paper, we applied STE on high-frame-rate B-mode images obtained with a specific MoCo technique to quantify the 2-D motion and tissue velocities of the left ventricle. The method was first validated in vitro and then evaluated in vivo in the four-chamber view of 10 volunteers. High-contrast high-resolution B-mode images were constructed at 500 frames/s. The sequences were generated with a Verasonics scanner and a 2.5-MHz phased array. The 2-D motion was estimated with standard cross correlation combined with three different subpixel adjustment techniques. The estimated in vitro velocity vectors derived from STE were consistent with the expected values, with normalized errors ranging from 4% to 12% in the radial direction and from 10% to 20% in the cross-range direction. Global longitudinal strain of the left ventricle was also obtained from STE in 10 subjects and compared to the results provided by a clinical scanner: group means were not statistically different ( $p$ value = 0.33). The in vitro and in vivo results showed that MoCo enables preservation of the myocardial speckles and in turn allows high-frame-rate STE.

Low Variance Estimation of Backscatter Quantitative Ultrasound Parameters Using Dynamic Programming

Abstract: One of the main limitations of ultrasound imaging is that image quality and interpretation depend on the skill of the user and the experience of the clinician. Quantitative ultrasound (QUS) methods provide objective, system-independent estimates of tissue properties, such as acoustic attenuation and backscattering properties of tissue, which are valuable as objective tools for both diagnosis and intervention. Accurate and precise estimation of these properties requires correct compensation for intervening tissue attenuation. Prior attempts to estimate intervening-tissue attenuation based on minimizing cost functions that compared backscattered echo data to models have resulted in limited precision and accuracy. To overcome these limitations, in this paper, we incorporate the prior information of piecewise continuity of QUS parameters as a regularization term into our cost function. We further propose to calculate this cost function using dynamic programming (DP), a computationally efficient optimization algorithm that finds the global optimum. Our results on tissue-mimicking phantoms show that DP substantially outperforms a published least squares method in terms of both estimation bias and variance.

Real-Time Blood Velocity Vector Measurement Over a 2-D Region

Abstract: Quantitative blood velocity measurements, as currently implemented in commercial ultrasound scanners, are based on pulsed-wave (PW) spectral Doppler and are limited to detect the axial component of the velocity in a single sample volume. On the other hand, vector Doppler methods produce angle-independent estimates by, e.g., combining the frequency shifts measured from different directions. Moreover, thanks to the transmission of plane waves, the investigation of a 2-D region is possible with high temporal resolution, but, unfortunately, the clinical use of these methods is hampered by the massive calculation power required for their real-time execution. In this paper, we present a novel approach based on the transmission of plane waves and the simultaneous reception of echoes from 16 distinct subapertures of a linear array probe, which produces eight lines distributed over a 2-D region. The method was implemented on the ULAO-OP 256 research scanner and tested both in phantom and in vivo . A continuous real-time refresh rate of 36 Hz was achieved in duplex combination with a standard B-mode at pulse repetition frequency of 8 kHz. Accuracies of −11% on velocity and of 2°on angle measurements have been obtained in phantom experiments. Accompanying movies show how the method improves the quantitative measurements of blood velocities and details the flow configurations in the carotid artery of a volunteer.

Advanced Satellite-Based Frequency Transfer at the 10 −16 Level

Abstract: Advanced satellite-based frequency transfers by two-way carrier-phase (TWCP) and integer precise point positioning have been performed between the National Institute of Information and Communications Technology and Korea Research Institute of Standards and Science. We confirm that the disagreement between them is less than $1\times 10^{-16}$ at an averaging time of several days. In addition, an overseas frequency ratio measurement of Sr and Yb optical lattice clocks was directly performed by TWCP. We achieved an uncertainty at the mid-10−16 level after a total measurement time of 12 h. The frequency ratio was consistent with the recently reported values within the uncertainty.

On the Effects of Spatial Sampling Quantization in Super-Resolution Ultrasound Microvessel Imaging

Abstract: Ultrasound super-resolution (SR) microvessel imaging technologies are rapidly emerging and evolving. The unprecedented combination of imaging resolution and penetration promises a wide range of preclinical and clinical applications. This paper concerns spatial quantization error in SR imaging, a common issue that involves a majority of current SR imaging methods. While quantization error can be alleviated by the microbubble localization process (e.g., via upsampling or parametric fitting), it is unclear to what extent the localization process can suppress the spatial quantization error induced by discrete sampling. It is also unclear when low spatial sampling frequency will result in irreversible quantization errors that cannot be suppressed by the localization process. This paper had two goals: 1) to systematically investigate the effect of quantization in SR imaging and establish principles of adequate SR imaging spatial sampling that yield minimal quantization error with proper localization methods and 2) to compare the performance of various localization methods and study the level of tolerance of each method to quantization. We conducted experiments on a small wire target and on a microbubble flow phantom. We found that the Fourier analysis of an oversampled spatial profile of the microbubble signal could provide reliable guidance for selecting beamforming spatial sampling frequency. Among various localization methods, parametric Gaussian fitting and centroid-based localization on upsampled data had better microbubble localization performance and were less susceptible to quantization error than peak intensity-based localization methods. When spatial sampling resolution was low, parametric Gaussian fitting-based localization had the best performance in suppressing quantization error, and could produce acceptable SR microvessel imaging with no significant quantization artifacts. The findings from this paper can be used in practice to help intelligently determine the minimum requirement of spatial sampling for robust microbubble localization to avoid adding or even reduce the burden of computational cost and data storage that are commonly associated with SR imaging.

Full Wavefield Analysis and Damage Imaging Through Compressive Sensing in Lamb Wave Inspections

Abstract: One of the main challenges faced by the structural health monitoring community is acquiring and processing huge sets of acoustic wavefield data collected from sensors, such as scanning laser Doppler vibrometers or ultrasonic scanners. In fact, extracting information that allows the estimation of the damage condition of a structure can be a time-consuming process. This paper presents a damage detection and localization technique based on a compressive sensing algorithm, which significantly allows us to reduce the acquisition time without losing in detection accuracy. The proposed technique exploits the sparsity of the wavefield in different representation domains, such as those spanned by wave atoms, curvelets, and Fourier exponentials to recover the full wavefield and, at the same time, to infer the damage location, based on comparison between the wavefield reconstructions produced by the different representation domains. The procedure is applied to three different setups related to an aluminum plate with a notch, a glass fiber reinforced polymer plate with a notch, and a composite plate with a delamination. The results show that the technique can be applied in a variety of structural components to reduce acquisition time and achieve high performance in defect detection and localization by removing up to 80% of the Nyquist sampling grid.

Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction

Abstract: Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution to the image reconstruction problem. An alternative to DAS consists in using iterative techniques, which require both an accurate measurement model and a strong prior on the image under scrutiny. Toward this goal, much effort has been deployed in formulating models for US imaging, which usually require a large amount of memory to store the matrix coefficients. We present two different techniques, which take advantage of fast and matrix-free formulations derived for the measurement model and its adjoint, and rely on sparsity of US images in well-chosen models. Sparse regularization is used for enhanced image reconstruction. Compressed beamforming exploits the compressed sensing framework to restore high-quality images from fewer raw data than state-of-the-art approaches. Using simulated data and in vivo experimental acquisitions, we show that the proposed approach is three orders of magnitude faster than non-DAS state-of-the-art methods, with comparable or better image quality.

Loss Mechanisms Determining the Quality Factors in Quartz Tuning Forks Vibrating at the Fundamental and First Overtone Modes

Abstract: Quartz tuning forks (QTFs) are piezo-transducers that have been implemented for numerous applications, such as chemical gas sensing, atomic force microscopy, rheology, and industrial process control. The most important parameter for QTFs’ sensing application is the resonance quality factor (Q-factor). An experimental investigation and theoretical analysis of the influence of QTFs’ geometries on the Q-factor of the flexural fundamental and first overtone resonance modes are reported. The resonance frequencies and related Q-factors for five different QTFs have been measured. The QTF response was recorded at different air pressures to investigate the influence of the surrounding medium on the Q-factor. A data analysis demonstrated that air viscous damping is the dominant energy dissipation mechanism for both flexural modes. Thermoelastic and support losses are additional contributions that depend on the QTF geometry. A study of the QTF damping mechanism dependence upon the prong geometry is also provided.

Realistic Vendor-Specific Synthetic Ultrasound Data for Quality Assurance of 2-D Speckle Tracking Echocardiography: Simulation Pipeline and Open Access Database

Abstract: Two-dimensional (2-D) echocardiography is the modality of choice in the clinic for the diagnosis of cardiac disease. Hereto, speckle tracking (ST) packages complement visual assessment by the cardiologist by providing quantitative diagnostic markers of global and regional cardiac function (e.g., displacement, strain, and strain-rate). Yet, the reported high vendor-dependence between the outputs of different ST packages raises clinical concern and hampers the widespread dissemination of the ST technology. In part, this is due to the lack of a solid commonly accepted quality assurance pipeline for ST packages. Recently, we have developed a framework to benchmark ST algorithms for 3-D echocardiography by using realistic simulated volumetric echocardiographic recordings. Yet, 3-D echocardiography remains an emerging technology, whereas the compelling clinical concern is, so far, directed to the standardization of 2-D ST only. Therefore, by building upon our previous work, we present in this paper a pipeline to generate realistic synthetic sequences for 2-D ST algorithms. Hereto, the synthetic cardiac motion is obtained from a complex electromechanical heart model, whereas realistic vendor-specific texture is obtained by sampling a real clinical ultrasound recording. By modifying the parameters in our pipeline, we generated an open-access library of 105 synthetic sequences encompassing: 1) healthy and ischemic motion patterns; 2) the most common apical probe orientations; and 3) vendor-specific image quality from seven different systems. Ground truth deformation is also provided to allow performance analysis. The application of the provided data set is also demonstrated in the benchmarking of a recent academic ST algorithm.

Hierarchical Cascading Algorithm for 2-D FEM Simulation of Finite SAW Devices

Abstract: Application of the finite-element method (FEM) for the simulation of surface acoustic wave (SAW) devices has been constrained by the large number of degrees of freedom required, resulting in large memory usage and long computation times. We propose a new 2-D algorithm that takes advantage of the periodic structure typical of SAW devices. The device is partitioned into small, repeatedly occurring building blocks. Only unique building blocks are simulated with FEM. The device geometry is presented as a hierarchical tree of cascading operations, where smaller blocks are combined into larger blocks. This is equivalent to the full FEM simulation of the device, implying the drastic reduction of memory consumption and simulation time for structures with a high degree of periodicity. The method is verified against FEM/BEM-based software. To ensure accurate and efficient simulation, the boundary conditions should be chosen according to the anisotropy of the substrate crystal.

Robust Short-Lag Spatial Coherence Imaging

Abstract: Short-lag spatial coherence (SLSC) imaging displays the spatial coherence between backscattered ultrasound echoes instead of their signal amplitudes and is more robust to noise and clutter artifacts when compared with traditional delay-and-sum (DAS) B-mode imaging. However, SLSC imaging does not consider the content of images formed with different lags, and thus does not exploit the differences in tissue texture at each short-lag value. Our proposed method improves SLSC imaging by weighting the addition of lag values (i.e., M-weighting) and by applying robust principal component analysis (RPCA) to search for a low-dimensional subspace for projecting coherence images created with different lag values. The RPCA-based projections are considered to be denoised versions of the originals that are then weighted and added across lags to yield a final robust SLSC (R-SLSC) image. Our approach was tested on simulation, phantom, and in vivo liver data. Relative to DAS B-mode images, the mean contrast, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) improvements with R-SLSC images are 21.22 dB, 2.54, and 2.36, respectively, when averaged over simulated, phantom, and in vivo data and over all lags considered, which corresponds to mean improvements of 96.4%, 121.2%, and 120.5%, respectively. When compared with SLSC images, the corresponding mean improvements with R-SLSC images were 7.38 dB, 1.52, and 1.30, respectively (i.e., mean improvements of 14.5%, 50.5%, and 43.2%, respectively). Results show great promise for smoothing out the tissue texture of SLSC images and enhancing anechoic or hypoechoic target visibility at higher lag values, which could be useful in clinical tasks such as breast cyst visualization, liver vessel tracking, and obese patient imaging.

Characterization of Viscoelastic Materials Using Group Shear Wave Speeds

Abstract: Recent investigations of viscoelastic properties of materials have been performed by observing shear wave propagation following localized, impulsive excitations, and Fourier decomposing the shear wave signal to parameterize the frequency-dependent phase velocity using a material model. This paper describes a new method to characterize viscoelastic materials using group shear wave speeds $V_{\mathrm{ disp}}$ , $V_{\mathrm{ vel}}$ , and $V_{\mathrm{ acc}}$ determined from the shear wave displacement, velocity, and acceleration signals, respectively. Materials are modeled using a two-parameter linear attenuation model with phase velocity $c_{200}$ and dispersion slope $c^{\prime }_{200}$ at a reference frequency of 200 Hz. Analytically calculated lookup tables are used to determine the two material parameters from pairs of measured group shear wave speeds. Green’s function calculations are used to validate the analytic model. Results are reported for measurements in viscoelastic and approximately elastic phantoms and demonstrate good agreement with phase velocities measured using Fourier analysis of the measured shear wave signals. The calculated lookup tables are relatively insensitive to the excitation configuration. While many commercial shear wave elasticity imaging systems report group shear wave speeds as the measures of material stiffness, this paper demonstrates that differences $\Delta V_{\mathrm{ vd} = V_{\mathrm{ vel}} - V_{\mathrm{ disp}}}$ , $\Delta V_{\mathrm{ ad} = V_{\mathrm{ acc}} - V_{\mathrm{ disp}}}$ , and $\Delta V_{\mathrm{ av} = V_{\mathrm{ acc}} - V_{\mathrm{ vel}}}$ of group speeds are first-order measures of the viscous properties of materials.

Dynamic Time Warping Temperature Compensation for Guided Wave Structural Health Monitoring

Abstract: Guided wave structural health monitoring is widely researched for remotely inspecting large structural areas. To detect, locate, and characterize damage, guided wave methods often compare data to a baseline signal. Yet, environmental variations create large differences between the baseline and the collected measurements. These variations hide damage signatures and cause false detection. Temperature compensation algorithms, such as baseline signal stretch and the scale transform have been used to optimally realign data to a baseline. While these methods are effective in some conditions, their performance deteriorates in the presence of large temperature variations, long propagation distances, and high frequencies. In this paper, we use dynamic time warping to better align guided wave data and to overcome these errors. When compared with stretch-based methods, we show that the dynamic time warping is more robust to the above-mentioned errors and more accurately detects damage with weak ultrasonic signatures.

Directivity and Frequency-Dependent Effective Sensitive Element Size of Needle Hydrophones: Predictions From Four Theoretical Forms Compared With Measurements

Abstract: Directivity is a hydrophone specification that describes response as a function of angle of incidence. The goal of this study was to compare, in the context of needle hydrophones, the commonly used rigid baffle model for hydrophone directivity to three alternative models: soft baffle, unbaffled (UB), and rigid piston (RP). Directivity measurements were performed at 1, 2, 3, 4, 6, 8, and 10 MHz from ±7° in two orthogonal planes for two ceramic and two polymer needle hydrophones with nominal geometrical sensitive element diameters of 200, 400, 600, and 1000 $\mu \text{m}$ . Effective hydrophone sensitive element radius was estimated by least-squares fitting the four models to directivity measurement data using the sensitive element radius (a) as an adjustable parameter. For $ka$ > 4 (where $k=2\pi /\lambda$ and $\lambda$ = wavelength), the RP model outperformed the other three models. For $ka=1$ , the average error in estimated sensitive element radius was 7% [95% confidence interval (CI): 3%–12%] for the RP model while the lowest average error by the other three models was 46% (95% CI: 38%–54%) for the UB model.

Directivity and Frequency-Dependent Effective Sensitive Element Size of a Reflectance-Based Fiber-Optic Hydrophone: Predictions From Theoretical Models Compared With Measurements

Abstract: The goal of this work was to measure the directivity of a reflectance-based fiber-optic hydrophone at multiple frequencies and to compare it to four theoretical models: rigid baffle (RB), rigid piston (RP), unbaffled (UB), and soft baffle (SB). The fiber had a nominal 105- $\mu \text{m}$ diameter core and a 125- $\mu \text{m}$ overall diameter (core + cladding). Directivity measurements were performed at 2.25, 3.5, 5, 7.5, 10, and 15 MHz from ±90° in two orthogonal planes. Effective hydrophone sensitive element radius was estimated by least-squares fitting the four models to the directivity measurements using the sensitive element radius as an adjustable parameter. Over the range from 2.25 to 15 MHz, the average magnitudes of differences between the effective and nominal sensitive element radii were 59% ± 49% (RB), 10% ± 5% (RP), 46% ± 38% (UB), and 71% ± 19% (SB). Therefore, the directivity of a reflectance-based fiber-optic hydrophone may be best estimated by the RP model.