High-Resolution Ultrasound Imaging With Unified Pixel-Based Beamforming

Stretchable Ultrasound Metalens for Biomedical Zoom Imaging and Bone Quality Assessment with Subwavelength Resolution

Ultrasound imaging is extensively used in biomedical science and clinical practice. Imaging resolution and tunability of imaging plane are key performance indicators, but both remain challenging to be improved due to the longer wavelength compared with light and the lack of zoom lens for ultrasound. Here, the ultrasound zoom imaging based on a stretchable planar metalens that simultaneously achieves the subwavelength imaging resolution and dynamic control of the imaging plane is reported. The proposed zoom imaging ultrasonography enables precise bone fracture diagnosis and comprehensive osteoporosis assessment. Millimeter-scale microarchitectures of the cortical bones at different depths can be selectively imaged with a 0.6-wavelength resolution. The morphological features of bone fractures, including the shape, size and position, are accurately detected. Based on the extracted ultrasound information of cancellous bones with healthy matrix, osteopenia and osteoporosis, a multi-index osteoporosis evaluation method is developed. Furthermore, it provides additional biological information in aspects of bone elasticity and attenuation to access the comprehensive osteoporosis assessment. The soft metalens also features flexibility and biocompatibility for preferable applications on wearable devices. This work provides a strategy for the development of high-resolution ultrasound biomedical zoom imaging and comprehensive bone quality diagnosis system.

Improved Spatiotemporal Resolution in Echocardiography Using Mixed Geometry Imaging Sequences

Cardiac ultrasound seeks to image the most dynamic environment in the body-the moving heart. Many modern ultrasound imaging techniques address the tradeoff between spatial and temporal resolution using either narrow focused beams or with broad beam, synthetic aperture (SA) sequences that have been shown to suffer from motion artifacts. Retrospective encoding for conventional ultrasound sequences (REFoCUS) unifies the processing of these various geometric sequences, but the motion sensitivity of this approach has yet to be investigated. We hypothesize that a "mixed sequence" enabled by the REFoCUS method incorporating several beam geometries may better resolve cardiac motion over a wide field of view (FOV) and at a high frame rate. First, the motion sensitivity of REFoCUS was evaluated in simulation for several focused and broad transmit profiles. Focused transmissions resolve both lateral and axial motion much more effectively than broad transmissions, with performance similar to conventional beamforming techniques. Second, a mixed sequence was designed that insonifies the full field-of-view with plane wave (PW) transmissions and key moving targets with focused transmissions. This mixed sequence was tested in simulation and in vivo and was used to image the heart as well as the liver, a low-motion control. By combining a sparse PW sequence ( n=60 ) with a small group of targeted focused transmissions ( n = 10), the anterior mitral valve leaflet (AML) at its peak observed velocity was better resolved. We believe that mixed sequences have strong potential to resolve cardiac motion at clinically relevant frame rates.

Pixel-based approach to delay multiply and sum beamforming in combination with Wiener filter for improving ultrasound image quality

Unified pixel-based (PB) beamforming has been implemented for ultrasound imaging, offering significant enhancements in lateral resolution compared to the conventional dynamic focusing. However, it still suffers from clutter and off-axis artifacts, limiting the contrast resolution. This paper proposes an efficient method to improve image quality by integrating filtered delay multiply and sum (F-DMAS) into the framework. This hybrid strategy incorporates the spatial coherence of the received data into the beamforming process to improve contrast resolution and clutter rejection in the generated image. We also integrate a Wiener filter to suppress the spatiotemporal spreading using signals echoed from a single scatterer at the transmit focus as a kernel for the deconvolution. The Wiener filter is applied to the received waveforms before performing the hybrid strategy. The Wiener filter is shown to reduce interference due to the interaction between the excitation pulse and the transfer functions of the transducer elements, thus benefiting the axial resolution of the generated images. We validate the proposed method and compare it with other beamforming strategies through a series of experiments, including simulation, phantom, and in vivo studies. The results show that our approach can substantially improve both spatial resolution and contrast over the unified PB algorithm, while still maintaining the good features of this beamformer. The simplicity and good performance of our method show its potential for use in clinical applications.

An adaptive beamformer based on dynamic phase coherence factor for pixel-based medical ultrasound imaging

BACKGROUND

Pixel-based beamforming realizes dynamic focusing at the pixel level with a focused beam by assuming that the received signals are composed of spherical pulses. Far-focused pixel-based (FPB) imaging was proposed to avoid artifacts around the focal depth. However, the contrast improvement is limited.

OBJECTIVE

We propose an adaptive weighting method based on dynamic phase coherence factor (DPCF) to improve the image contrast while preserving the speckle pattern.

METHODS

The phase variation is dynamically estimated based on the noise energy proportion of echo signals and it is used to calculate phase coherence weights for suppressing interference and preserving desired signals. A depth-dependent parameter is designed for DPCF to enhance the performance of noise and clutter suppression in the far-field region. We further use the subarray averaging technique to smooth the speckle texture.

RESULTS

The proposed method was evaluated on simulated, phantom experimental, and in vivo data. Results show that, compared with the phase coherence factor (PCF) based method, DPCF respectively leads to average CR improvements by more than 60% and 24% in simulation and experiment, while obtaining an improved speckle signal-to-noise ratio.

CONCLUSIONS

The proposed method is a potentially valuable approach to obtaining high-quality ultrasound images in clinical applications.

Comparison of spatial encodings for ultrasound imaging

Ultrasound pulse sequencing and receive signal focusing work hand-in-hand to determine image quality. These are commonly linked by geometry, for example using focused beams or planewaves in transmission paired with appropriate time-of-flight calculations for focusing. Spatial encoding allows a broader class of array transmissions but requires decoding of the recorded echoes before geometric focusing can be applied. Recent work has expanded spatial encoding to include not only element apodizations but also element time delays. This powerful technique allows for a unified beamforming strategy across different pulse sequences and increased flexibility in array signal processing given access to estimates of individual transmit element signals, but trade-offs in image quality between these encodings has not been previously studied. We evaluate in simulation several commonly used time delay and amplitude encodings and investigate optimization of the parameter space for each. Using signal-to-noise ratio, point resolution, and lesion detectability we found trade-offs between focused beams, planewaves, and Hadamard weight encodings. Beams with broader geometries maintained a wider field-of-view after decoding at the cost of signal-to-noise ratio (SNR) and lesion detectability. Focused beams and planewaves showed slightly reduced resolution compared to Hadamard weights in some cases, especially close to the array. We also found overall degraded image quality using random weight or random delay encodings. We validate these findings with experimental phantom imaging for select cases. We believe that these findings provide a starting point for sequence optimization and for improved image quality using the spatial encoding approach for imaging.

The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia's frequency-wavenumber (f-k), Lu's f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia's f-k, Lu's f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.

Fourier Beamformation for Convex-Array Diverging Wave Imaging Using Virtual Sources

Convex probes have been widely used in clinical abdominal imaging for providing deep penetration and wide field of view. Ultrafast imaging modalities have been studied extensively in the ultrasound community. Specifically, broader wavefronts, such as plane wave and spherical wave, are used for transmission. For convex array, spherical wavefront can be simply synthesized by turning all elements simultaneously. Due to the lack to transmit focus, the image quality is suboptimal. One solution is to adopt virtual sources behind the transducer and compound corresponding images. In this work, we propose two novel Fourier-domain beamformers (vs1 and vs2) for nonsteered diverging wave imaging and an explicit interpolation scheme for virtual-source-based steered diverging wave imaging using a convex probe. The received echoes are first beamformed using the proposed beamformers and then interpolated along the range axis. A total of 31 virtual sources located on a circular line are used. The lateral resolution, the contrast ( C ), and the contrast-to-noise ratio (CNR) are evaluated in simulations, phantom experiments, ex vivo imaging of the bovine heart, and in vivo imaging of the liver. The results show that the two proposed Fourier-domain beamformers give higher contrast than dynamic receive focusing (DRF) with better resolution. In vitro results demonstrate the enhancement on CNR: 6.7-dB improvement by vs1 and 5.9-dB improvement by vs2. Ex vivo imaging experiments on the bovine heart validate the CNR enhancements by 8.4 dB (vs1) and 8.3 dB (vs2). In vivo imaging on the human liver also reveals 6.7- and 5.5-dB improvements of CNR by vs1 and vs2, respectively. The computation time of vs1 and vs2, depending on the image pixel number, is shortened by 2-73 and 4-216 times than the DRF.

Improved ultrasound image quality with pixel-based beamforming using a Wiener-filter and a SNR-dependent coherence factor

Pixel-based beamforming generates focused data by assuming that the waveforms received on a linear transducer array are composed of spherical pulses. It does not take into account the spatiotemporal spread in the data from the length of the excitation pulse or from the transfer functions of the transducer elements. As a result, these beamformers primarily have impacts on lateral, rather than axial, resolution. This paper proposes an efficient method to improve the axial resolution for pixel-based beamforming. We extend our field pattern analysis and show that the received waveforms should be passed through a Wiener filter before being used in the coherent pixel-based beamformer. This filter is designed based on signals echoed from a single scatterer at the transmit focus. The beamformer output is then combined with a coherence factor, that is adaptive to the signal-to-noise ratio, to improve the image contrast and suppress artifacts that have arisen during the filtering process. We validate the proposed method and compare it with other beamforming strategies using a series of experiments, including simulation, phantom and in vivo studies. It is shown to offer significant improvements in axial resolution and contrast over coherent pixel-based beamforming, as well as other spatial filters derived from synthetic aperture imaging. The method also demonstrates robustness to modeling errors in the experimental data. Overall, the imaging results show that the proposed approach has the potential to be of value in clinical applications.

Use of Intertransmission Coherence for Haze Artifact Suppression in Cardiovascular Synthetic Aperture Ultrasound Imaging

Synthetic aperture (SA) beamforming is a principal technology of modern medical ultrasound imaging. In that the use of focused transmission provides superior signal-to-noise ratio (SNR) and is promising for cardiovascular diagnosis at the maximum imaging depth of about 160 mm. But there is a pitfall in increasing the frame rate to more than 80 frames per second (frames/s) without image degradation by the haze artifact produced when the transmit foci (SA virtual sources) placed within the imaging field. We hypothesize that the source of this artifact is a grating lobe caused by coarse (decimated) multiple transmission and manifesting in the low brightness region in the accelerated-frame-rate images. We propose an intertransmission coherence factor (ITCF) method suppressing haze artifacts caused by coarse-pitch multiple transmission. The method is expected to suppress the image blurring because the SA grating lobe signal is less coherent than the main lobe signals. We evaluated an ITCF algorithm for suppressing the grating artifact when the transmission pitch is up to four times larger than the normal pitch (equivalent to 160 frames/s). In in-vitro and in-vivo experiments, we demonstrated the strong relation of haze artifact with the grating lobe due to the coarse-pitch transmission. Then, we confirmed that the ITCF method suppresses the haze artifact of a human heart by 15 dB while preserving the spatial resolution. The ITCF method combined with focused transmission SA beamforming is a valid method for getting cardiovascular ultrasound B-mode images without making a compromise in the trade-off relationship between the frame rate and the SNR.

Ultrasound far-focused pixel-based imaging using Wiener postfilter scaled by adjustable zero-cross factor

Synthetic aperture (SA) imaging can provide a uniform lateral resolution but an insufficient signal-to-noise ratio (SNR). SA method with bidirectional pixel-based focusing (SA-BiPBF) has the ability to obtain a higher quality image than conventional SA imaging. In this paper, an enhanced SA-BiPBF named full aperture received far-focused pixel-based (FrFPB) is firstly proposed to obtain a high resolution image. An adjustable zero-cross factor scaled Wiener postfilter (AZFsW) is then implemented in FrFPB for improving contrast ratio (CR). The adjustable zero-cross factor is calculated using the polarity of echo signals sequence with an adjustable coefficient σ to estimate the signal coherence, and it is combined with Wiener postfilter to obtain a good capability of noise reduction and background speckle pattern preservation. Simulation and experiments have been conducted to evaluate the imaging performance of the proposed methods. Results show that FrFPB can obviously improve the resolution in comparison with SA-BiPBF, and contrast-to-noise ratio (CNR) and speckle signal-to-noise ratio (sSNR) are retained. In addition, AZFsW can achieve a much higher CR than SA-BiPBF. When σ is 0.6, the CR improvement is 96.7% in simulation, 78.7% in phantom experiment, and 49.2% in in-vivo experiment. To evaluate the imaging performance of AZFsW, coherence factor, conventional Wiener postfilter, and scaled Wiener postfilter are implemented. The imaging results show that when σ is in the range of [0.6, 0.7], AZFsW exhibits a satisfying comprehensive imaging performance.

User Parameter-Free Minimum Variance Beamformer in Medical Ultrasound Imaging

The minimum variance beamformer (MVB) is a well-known adaptive beamformer in medical ultrasound imaging. Accurate estimation of the covariance matrix has a great effect on the performance of the MVB. In adaptive ultrasound imaging, parameters such as the subarray length, the number of samples used for temporal averaging, and the value of diagonal loading (DL) have the main role in the true estimation of the covariance matrix. The optimal values for these parameters are different from one scenario to another one. Thus, the MVB is not a parameter-free method, and its behavior is scenario-dependent. In the field of telecommunications and radar, the shrinkage method was proposed to determine the DL factor, but no method has been provided yet to determine other parameters. In this article, an adaptive approach is developed to determine the MVB parameters, which is completely independent of the user. The minimum variance variable loading along with the modified shrinkage (MVVL-MSh) algorithm is introduced to adaptively calculate the optimal DL. Also, two methods based on the coherence factor (CF) are proposed to determine the subarray length in the spatial smoothing and the number of samples required for temporal averaging. The performance of the proposed methods is evaluated using simulated and experimental RF data. It is shown that the methods preserve the contrast and improve the resolution by about 35% and 38% compared to the MV having a fix loading coefficient and the MV-Sh algorithm.

Minimum Variance Combined With Modified Delay Multiply-and-Sum Beamforming for Plane-Wave Compounding

Plane-wave compounding is an active topic of research in ultrasound imaging because it is a promising technique for ultrafast ultrasound imaging. Unfortunately, due to the data-independent nature of the traditional compounding method, it imposes a fundamental limit on image quality. To address this issue, adaptive beamformers have been implemented in the compounding procedure. In this article, a new adaptive beamformer for the 2-D data set obtained from multiple plane-wave transmissions is investigated. In the proposed scheme, the minimum variance (MV) weights are applied to the backscattered echoes. Then, the final image is obtained by employing a modified version of the delay multiply-and-sum (DMAS) beamformer in the coherent compounding. The results demonstrate that the presented MV-DMAS scheme outperforms the conventional coherent compounding in both terms of resolution and contrast. It also offers improvements over the 2-D-DMAS and some MV-based methods presented in the literature, such that it achieves at least 20.9% enhancement in sidelobe reduction compared with the best result of MV-based methods. Also, by the proposed method, the in vivo study shows an improved generalized contrast-to-noise ratio (GCNR) that implies a higher probability of lesion detection.

Resolution and Speckle Reduction in Cardiac Imaging

Cardiac imaging depends on clear visualization of several different structural and functional components to determine left ventricular and overall cardiac health. Ultrasound imaging is confounded by the characteristic speckle texture resulting from subwavelength scatterers in tissues, which is similar to a multiplicative noise on underlying tissue structure. Reduction of this texture can be achieved through physical means, such as spatial or frequency compounding, or through adaptive image processing. Techniques in both categories require a tradeoff of resolution for speckle texture reduction, which together contribute to overall image quality and diagnostic value. We evaluate this tradeoff for cardiac imaging tasks using spatial compounding as an exemplary speckle reduction method. Spatial compounding averages the decorrelated speckle patterns formed by views of a target from multiple subaperture positions to reduce the texture at the expense of active aperture size (and, in turn, lateral resolution). We demonstrate the use of a novel synthetic aperture focusing technique to decompose harmonic backscattered data from focused beams to their aperture-domain spatial frequency components to enable combined transmit and receive compounding. This tool allows the evaluation of matched data sets from a single acquisition over a wide range of spatial compounding conditions. We quantified the tradeoff between resolution and texture reduction in an imaging phantom and demonstrated improved lesion detectability with increasing levels of spatial compounding. We performed a cardiac ultrasound on 25 subjects to evaluate the degree of compounding useful for diagnostic imaging. Of these, 18 subjects were included in both qualitative and quantitative analysis. We found that compounding improved detectability of the endocardial border according to the generalized contrast-to-noise ratio in all cases, and more aggressive compounding made further improvements in ten out of 18 cases. Three expert reviewers evaluated the images for their usefulness in several diagnostic tasks and ranked four compounding conditions ("none," "low," "medium," and "high"). Contrary to the quantitative metrics that suggested the use of high levels of compounding, the reviewers determined that "low" was usually preferred (77.9%), while "none" or "medium" was selected in 21.2% of cases. We conclude with a brief discussion of the generalization of these results to other speckle reduction methods using the imaging phantom data.

Parallel Receive Beamforming Improves the Performance of Focused Transmit-Based Single-Track Location Shear Wave Elastography

Single-track location shear wave elastography (STL-SWEI) is robust against speckle-induced noise in shear wave speed (SWS) estimates; however, it is not immune to other incoherent sources of noise (such as electronic noise) that increases the variance in SWS estimates. Although estimation averaging enabled by parallel receive beamforming adequately suppresses these noise sources, these beamforming techniques often rely on broad transmit beams (plane or diverging). While broad beam approaches, such as plane-wave imaging, are becoming ubiquitous in research ultrasound systems, clinical systems usually employ focused transmit beams due to compatibility with hardware beamforming and deeper penetration. Consequently, improving the noise robustness of focused transmit-based STL-SWEI may enable easier translation to clinical scenarios. In this article, we experimentally evaluated the performance of parallel beamforming for STL-SWEI using fixed or multiple transmit focus. By imaging tissue-mimicking phantoms, we found that parallel beamforming improved the focal zone elastographic signal-to-noise ratio (SNR_e) by 40.9%. For a receive line spacing equivalent to transducer pitch, averaging estimates from three parallel lines produced peak SNR_e at the focal zone (25 mm), while, at the shallower regions (< 20 mm), a larger number of parallel lines (>7) were needed. Increasing the beamforming line density by a factor of 8 increased the focal zone SNR_e only by 13.2%. When SWS quantification was desirable at a fixed depth (such as within the push focal depth), using a deeper tracking focal zone enabled higher parallel line count and improved the peak SNR_e by 33%. The multifocusing strategy produced a lower SNR_e than the single-focus configurations. For a fixed tracking focal zone, a depth-dependent averaging based on the simulated transmit intensity adequately accounted for the transmit beamwidth. The results in this work demonstrated that STL-SWEI can be implemented using focused transmit beams with robust noise-suppression capability.

Lag-Based Filtered-Delay Multiply and Sum Beamformer Combined with Two Phase-Related Factors for Medical Ultrasound Imaging

A novel adaptive beamformer named filtered-delay multiply and sum (F-DMAS) has recently been proposed. Compared to the delay and sum (DAS) beamforming algorithm, F-DMAS can efficiently improve the resolution and contrast. However, the DAS can still be seen in the expansion of DMAS. Therefore, we rearrange the pair-wised signals in terms of lag in DMAS and then synthesize a lot of new signals. Thanks to the relationship between the spatial coherence and lag, these new signals can be thought of as sorted by the spatial coherence. Thus, we apply two phase-related factors, the polarity-based factor (PF) and the sign coherence factor (SCF), which are evaluated based on new signals, to weight the output of DMAS. The two approaches are consequently referred to as LAG-DMAS-PF and LAG-DMAS-SCF, respectively. The results show that, compared to F-DMAS and DAS, our proposed methods can improve the resolution and contrast to some extent without increasing too much computational complexity. In the comparison between LAG-DMAS-PF and LAG-DMAS-SCF, the latter has better performance, but the former can better protect image details.

Synthetic Aperture Focusing for Multi-Covariate Imaging of Sub-Resolution Targets

Coherence-based imaging methods suffer from reduced image quality outside the depth of field for focused ultrasound transmissions. Synthetic aperture methods can extend the depth of field by coherently compounding time-delayed echo data from multiple transmit events. Recently, our group has presented the Multi-covariate Imaging of Sub-resolution Targets (MIST), an estimation-based method to image the statistical properties of diffuse targets. MIST has demonstrated improved image quality over conventional delay-and-sum, but like many coherence-based imaging methods, suffers from limited depth of field artifacts. This article applies synthetic aperture focusing to MIST, which is evaluated using focused, plane-wave, and diverging-wave transmit geometries. Synthetic aperture MIST is evaluated in simulation, phantom, and in vivo applications, demonstrating consistent improvements in contrast-to-noise ratio (CNR) over conventional dynamic receive MIST outside the transmit depth of field, with approximately equivalent results between synthetic transmit geometries. In vivo synthetic aperture MIST images demonstrated 16.8 dB and 16.6% improvements in contrast and CNR, respectively, over dynamic receive MIST images, as well as 17.4 dB and 32.3% improvements over synthetic aperture B-Mode. MIST performance is characterized in the space of plane-wave imaging, where the total plane-wave count is reduced through coarse angular sampling or total angular span. Simulation and experimental results indicate wide applicability of MIST to synthetic aperture imaging methods.

The Impact of Acoustic Clutter on Large Array Abdominal Imaging

Abdominal imaging suffers from a particularly difficult acoustic environment-targets are located deep and overlying tissue layers with varying properties generate acoustic clutter. Increasing array size can overcome the penetration and lateral resolution problems in ideal conditions, but how the impact of clutter scales with increasing array extent is unknown and may limit the benefits in vivo. Previous ex vivo experimental work showed the promise of large arrays but was technically limited to a length of 6.4 cm and to only partial sampling of the array elements. We present an extension of those studies using the Fullwave simulation tool to create a 10 cm ×2 cm matrix array with full lateral element sampling. We used a numerical model of the abdomen based on the maps of tissue acoustical properties and found that propagation through the modeled abdominal layers generated on average 25.4 ns of aberration and 0.74 cm of reverberation clutter across the array extent. Growing the full aperture from 2 to 10 cm improved contrast by 8.6 dB and contrast-to-noise ratio by 22.9% in addition to significantly improving target resolution. Alternative array strategies that may be useful for implementation-mismatched aperture sizes or a swept synthetic aperture-also produced improved quality with growing aperture size. These results motivate the development of larger diagnostic imaging arrays for the purpose of high-resolution imaging in challenging environments.

High Resolution Minimum Variance Beamformer With Low Complexity in Medical Ultrasound Imaging

Although the minimum variance beamformer (MVB) shows a significant improvement in resolution and contrast in medical ultrasound imaging, its high computational complexity is a major problem in a real-time imaging system. Therefore, it seems necessary to propose a new method with a lower computational complexity that preserves the advantages of the MVB. In this paper, the MVB was implemented with a partial generalized sidelobe canceler (GSC) with a blocking matrix based on our previous study, which projected the incoming signals to a lower dimensional space. The partial GSC separated the weight vector into one fixed and one adaptive weight, whereby the optimization could be performed with lower complexity on the adaptive part. In addition, this dimension reduction allowed us to increase the length of the subarray when using a spatial smoothing method, which was used to decorrelate the incoming signals. The subarray length was limited to half the length of the full array size in the ordinary MVB, while the proposed beamformer could cross over this limitation. The results demonstrated that the point spread function of the proposed beamformer was about 6.3 times narrower than the classic MVB, while the contrast was almost saved. These results were achieved with linear computational complexity by the proposed method, while it was cubic for the MVB. For a sample scenario, the proposed method needed only 1.8% of the required ops of the MVB.

Comparison of virtual source synthetic aperture beamforming with an element-based model

Ultrasound beamforming relies on models of propagation to convert samples of the backscattered field through time into spatial image samples. The most common model is straight-line propagation of a focused wave, assuming a narrow steered and focused beam that propagates along a selected direction. The reconstructed image suffers from defocusing, reduced signal-to-noise ratio (SNR), and contrast loss away from the focus. "Virtual source" methods coherently combine the recorded data from multiple transmissions to form a synthetic transmit focus by making geometric assumptions about the transmissions. These also include diverging waves (virtual source behind the array) and plane waves (virtual source at infinity). Retrospective encoding for conventional ultrasound sequences (REFoCUS) beamforming has been proposed to instead model transmission as the superposition of the responses of individual transmit elements on the transducer array and to efficiently estimate the "complete data set"-individual element transmit and receive responses. In addition to isolating individual element contributions, the result of this unifying framework is a high-SNR, two-way focused image from focused plane wave or diverging transmissions. No significant differences were observed for either SNR or image quality measured by contrast-to-noise ratio between the appropriate virtual source method and REFoCUS beamforming in simulation and experimental imaging.

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

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.

Double-Stage Delay Multiply and Sum Beamforming Algorithm Applied to Ultrasound Medical Imaging

In ultrasound (US) imaging, delay and sum (DAS) is the most common beamformer, but it leads to low-quality images. Delay multiply and sum (DMAS) was introduced to address this problem. However, the reconstructed images using DMAS still suffer from the level of side lobes and low noise suppression. Here, a novel beamforming algorithm is introduced based on expansion of the DMAS formula. We found that there is a DAS algebra inside the expansion, and we proposed use of the DMAS instead of the DAS algebra. The introduced method, namely double-stage DMAS (DS-DMAS), is evaluated numerically and experimentally. The quantitative results indicate that DS-DMAS results in an approximately 25% lower level of side lobes compared with DMAS. Moreover, the introduced method leads to 23%, 22% and 43% improvement in signal-to-noise ratio, full width at half-maximum and contrast ratio, respectively, compared with the DMAS beamformer.

Enhanced linear-array photoacoustic beamforming using modified coherence factor

Photoacoustic imaging (PAI) is a promising medical imaging modality providing the spatial resolution of ultrasound imaging and the contrast of optical imaging. For linear-array PAI, a beamformer can be used as the reconstruction algorithm. Delay-and-sum (DAS) is the most prevalent beamforming algorithm in PAI. However, using DAS beamformer leads to low-resolution images as well as high sidelobes due to nondesired contribution of off-axis signals. Coherence factor (CF) is a weighting method in which each pixel of the reconstructed image is weighted, based on the spatial spectrum of the aperture, to mainly improve the contrast. We demonstrate that the numerator of the formula of CF contains a DAS algebra and propose the use of a delay-multiply-and-sum beamformer instead of the available DAS on the numerator. The proposed weighting technique, modified CF (MCF), has been evaluated numerically and experimentally compared to CF. It was shown that MCF leads to lower sidelobes and better detectable targets. The quantitative results of the experiment (using wire targets) show that MCF leads to for about 45% and 40% improvement, in comparison with CF, in the terms of signal-to-noise ratio and full-width-half-maximum, respectively.

Recovery of the Complete Data Set From Focused Transmit Beams

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.

Improvements to ultrasonic beamformer design and implementation derived from the task-based analytical framework

The task-based framework, previously developed for beamformer comparison [Nguyen, Prager, and Insana, J. Acoust. Soc. Am. 140, 1048-1059 (2016)], is extended to design a new beamformer with potential applications in breast cancer diagnosis. The beamformer is based on a better approximation of the Bayesian strategy. It is a combination of the Wiener-filtered beamformer and an iterative process that adapts the generated image to specific features of the object. Through numerical studies, the new method is shown to outperform other beamformers drawn from the framework, but at an increase in computational cost. It requires a preprocessing step where the scattering field is segmented into regions with distinct statistical properties. Segmentation errors become a major limitation to the beamformer performance. All the beamformers under investigation are tested using data obtained from an instrumented ultrasound machine. They are implemented using a new time delay calculation, recently developed in the pixel-based beamforming studies presented here, which helps to overcome the challenge posed by the shift-variant nature of the imaging system. The efficacy of each beamformer is evaluated based on the quality of generated images in the context of the task-based framework. The in vitro results confirm the conclusions drawn from the simulations.

Ultrasound Pixel-Based Beamforming With Phase Alignments of Focused Beams

We previously developed unified pixel-based (PB) beamforming to generate high-resolution sonograms, based on field pattern analysis. In this framework, we found that the transmit waveshape away from the focus could be characterized by two spherical pulses. These correspond to the maximal and minimal distances from the imaging point to the active aperture. The beamformer uses this model to select the highest energy signals from backscattered data. A spatiotemporal interpolation formula is used to provide a smooth transition in regions near the focal depth where there is no dominant reflected pulse. In this paper, we show that the unified PB approach is less robust at lower center frequencies. The interpolated data is suboptimal for a longer transmit waveshape. As a result, the spatial resolution at the focal depth is lower than that in other regions. By further exploring the field pattern, we propose a beamformer that is more robust to variations in beamwidth. The new method, named coherent PB beamforming, aligns and compounds the pulse data directly in the transition regions. In simulation and phantom studies, the coherent PB approach is shown to outperform the unified PB approach in spatial resolution. It helps regain optimal resolution at the focal depth while still maintaining good image quality in other regions. We also demonstrate the new method on in vivo data where its improvements over the unified PB method are demonstrated on scanned objects with a more complicated structure.

Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging

Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely delay-multiply-and-sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging, was introduced to overcome the challenges in DAS. DMAS was used in PAI systems and it was shown that this algorithm results in resolution improvement and sidelobe degrading. However, DMAS is still sensitive to high levels of noise, and resolution improvement is not satisfying. Here, we propose a novel algorithm based on DAS algebra inside DMAS formula expansion, double stage DMAS (DS-DMAS), which improves the image resolution and levels of sidelobe, and is much less sensitive to high level of noise compared to DMAS. The performance of DS-DMAS algorithm is evaluated numerically and experimentally. The resulted images are evaluated qualitatively and quantitatively using established quality metrics including signal-to-noise ratio (SNR), full-width-half-maximum (FWHM) and contrast ratio (CR). It is shown that DS-DMAS outperforms DAS and DMAS at the expense of higher computational load. DS-DMAS reduces the lateral valley for about 15 dB and improves the SNR and FWHM better than 13% and 30%, respectively. Moreover, the levels of sidelobe are reduced for about 10 dB in comparison with those in DMAS.

Minimum Variance Approaches to Ultrasound Pixel-Based Beamforming

We analyze the principles underlying minimum variance distortionless response (MVDR) beamforming in order to integrate it into a pixel-based algorithm. There is a challenge posed by the low echo signal-to-noise ratio (eSNR) when calculating beamformer contributions at pixels far away from the beam centreline. Together with the well-known scarcity of samples for covariance matrix estimation, this reduces the beamformer performance and degrades the image quality. To address this challenge, we implement the MVDR algorithm in two different ways. First, we develop the conventional minimum variance pixel-based (MVPB) beamformer that performs the MVDR after the pixel-based superposition step. This involves a combination of methods in the literature, extended over multiple transmits to increase the eSNR. Then we propose the coherent MVPB beamformer, where the MVDR is applied to data within individual transmits. Based on pressure field analysis, we develop new algorithms to improve the data alignment and matrix estimation, and hence overcome the low-eSNR issue. The methods are demonstrated on data acquired with an ultrasound open platform. The results show the coherent MVPB beamformer substantially outperforms the conventional MVPB in a series of experiments, including phantom and in vivo studies. Compared to the unified pixel-based beamformer, the newest delay-and-sum algorithm in [1], the coherent MVPB performs well on regions that conform to the diffuse scattering assumptions on which the minimum variance principles are based. It produces less good results for parts of the image that are dominated by specular reflections.