VLSI circuits for adaptive digital beamforming in ultrasound imaging

Beamforming (BF) in ultrasound (US) imaging has significant impact on the quality of the final image, controlling its resolution and contrast. Despite its low spatial resolution and contrast, delay-and-sum (DAS) is still extensively used nowadays in clinical applications, due to its real-time capabilities. The most common alternatives are minimum variance (MV) method and its variants, which overcome the drawbacks of DAS, at the cost of higher computational complexity that limits its utilization in real-time applications. In this paper, we propose to perform BF in US imaging through a regularized inverse problem based on a linear model relating the reflected echoes to the signal to be recovered. Our approach presents two major advantages: 1) its flexibility in the choice of statistical assumptions on the signal to be beamformed (Laplacian and Gaussian statistics are tested herein) and 2) its robustness to a reduced number of pulse emissions. The proposed framework is flexible and allows for choosing the right tradeoff between noise suppression and sharpness of the resulted image. We illustrate the performance of our approach on both simulated and experimental data, with in vivo examples of carotid and thyroid. Compared with DAS, MV, and two other recently published BF techniques, our method offers better spatial resolution, respectively contrast, when using Laplacian and Gaussian priors.

Applying the Capon adaptive beamformer in medical ultrasound imaging results in enhanced resolution by improving the interference-suppressing capabilities of the array. This improvement comes at the expense of an increased computational complexity. We have investigated the application of a beamspace adaptive beamformer for medical ultrasound imaging, which can be used to achieve reduced computational complexity with performance comparable to that of the Capon beamformer. The idea behind beamspace beamforming is that, instead of using the spatial statistics of the elements in the array to differentiate between signals and interference, we use the spatial statistics of a set of orthogonal beams, which are formed in different directions. This represents a shift from element space to beamspace. Because the majority of interference in medical ultrasound imaging is constrained to a limited spatial interval due to the focused transmit beam, this latter space can be reduced to a dimension that is lower than that of element space. We show, using simulations and experimental data, that this dimension can be selected as low as 3 while still achieving performance comparable to its element space counterpart.

Phase aberration correction for ultrasound imaging guided extracorporeal shock wave therapy (ESWT): Feasibility study

Plane-wave imaging (PWI) is a best way to improve the frame rate in ultrasound imaging. However, due to the lack of transmit focus in PWI, the image quality is poor. A novel coherent plane-wave compounding (CPWC) was proposed to handle this issue, but the increased plane waves (PWs) reduced the frame rate. Thus, we combine a novel Double-Stage Delay Multiply and Sum (DS-DMAS) beamformer, which is shown to be better to improve the image quality, with plane-wave compounding to analyze the performance in terms of resolution and contrast. The simulation tests are carried out to show that applying DS-DMAS beamformer can achieve better results even if the number of transmitted PWs are decreased.

Conventional ultrasound (US) imaging employs the delay and sum (DAS) receive beamforming with dynamic receive focus for image reconstruction due to its simplicity and robustness. However, the DAS beamforming follows a geometrical method of delay estimation with a spatially constant speed-of-sound (SoS) of 1540 m/s throughout the medium irrespective of the tissue in-homogeneity. This approximation leads to errors in delay estimations that accumulate with depth and degrades the resolution, contrast and overall accuracy of the US image. In this work, we propose a fast marching based DAS for focused transmissions which leverages the approximate SoS map to estimate the refraction corrected propagation delays for each pixel in the medium. The proposed approach is validated qualitatively and quantitatively for imaging depths of upto ∼ 11 cm through simulations, where fat layer-induced aberration is employed to alter the SoS in the medium. To the best of the authors' knowledge, this is the first work considering the effect of SoS on image quality for deeper imaging.Clinical relevance- The proposed approach when employed with an approximate SoS estimation technique can aid in overcoming the fat-induced signal aberrations and thereby in the accurate imaging of various pathologies of liver and abdomen.

Convolutive blind source separation and adaptive beamforming have similar goals and similar system structure. Both attempt to extract selected source signals from observed sensor mixtures by a filter array. However, time and frequency information are utilized in convolutive blind source separation while spatial information of source signals or sensor array is used in adaptive beamforming. In this paper, we start with a brief introduction of blind source separation and adaptive beamforming. Next, we review approaches combining spatial information used in beamforming with time/frequency processing used in convolutive blind source separation. We also present a new proposed combination approach and simulation results.

The present investigation introduces an adaptive beamforming scheme that separates the computationally intensive multidimensional beamforming into two simple modules, which are line and circular array beamformers. This approach minimizes the number of degrees of freedom associated with the adaptation process and provides near instantaneous convergence, which is essential for integrated active-passive sonar and medical ultrasound imaging applications. The proposed adaptive processing concept has been implemented in an integrated active-passive real-time sonar deploying a cylindrical array. Preliminary efforts include also the application of a line array adaptive beamformer in medical ultrasound imaging systems. Real data results from the adaptive and conventional beamforming outputs of the cylindrical array sonar system and the line array of the ultrasound system demonstrate the superior performance of the adaptive beamformer in suppressing the reverberation and cluttering effects in active sonar and medical ultrasound applications. Moreover, for passive sonar applications, the adaptive processing provides substantially improved angular resolution performance as compared with that of the conventional beamformer. Both these two performance improvements for a line and a cylindrical array sonar are of particular importance for mine hunting operations.

Wireless and sensorless 3D ultrasound imaging

Ultrasound (US) image guidance systems used in radiotherapy are typically calibrated for soft tissue applications, thus introducing errors in depth-from-transducer representation when used in media with a different speed of sound propagation (e.g. fat). This error is commonly referred to as the speed artifact. In this study we utilized a standard US phantom to demonstrate the existence of the speed artifact when using a commercial US image guidance system to image through layers of simulated body fat, and we compared the results with calculated/predicted values. A general purpose US phantom (speed of sound (SOS) = 1540 m s−1) was imaged on a multi-slice CT scanner at a 0.625 mm slice thickness and 0.5 mm × 0.5 mm axial pixel size. Target-simulating wires inside the phantom were contoured and later transferred to the US guidance system. Layers of various thickness (1–8 cm) of commercially manufactured fat-simulating material (SOS = 1435 m s−1) were placed on top of the phantom to study the depth-related alignment error. In order to demonstrate that the speed artifact is not caused by adding additional layers on top of the phantom, we repeated these measurements in an identical setup using commercially manufactured tissue-simulating material (SOS = 1540 m s−1) for the top layers. For the fat-simulating material used in this study, we observed the magnitude of the depth-related alignment errors resulting from the speed artifact to be 0.7 mm cm−1 of fat imaged through. The measured alignment errors caused by the speed artifact agreed with the calculated values within one standard deviation for all of the different thicknesses of fat-simulating material studied here. We demonstrated the depth-related alignment error due to the speed artifact when using US image guidance for radiation treatment alignment and note that the presence of fat causes the target to be aliased to a depth greater than it actually is. For typical US guidance systems in use today, this will lead to delivery of the high dose region at a position slightly posterior to the intended region for a supine patient. When possible, care should be taken to avoid imaging through a thick layer of fat for larger patients in US alignments or, if unavoidable, the spatial inaccuracies introduced by the artifact should be considered by the physician during the formulation of the treatment plan.

Medical ultrasound (US) imaging has been established as an essential diagnostic tool and US phantoms are fundamental tools to examine the performance of ultrasound imaging. We describe an inexpensive and reusable strategy to establish an ultrasound-imaging hydrogel phantom to satisfy researchers' requirement in this study. The result demonstrated that the transparent and durable ultrasound phantom contained two-vessel lumens, and its ultrasound imaging results were obtained with high-quality. Furthermore, we could observe a clear shape of the present word PKU on an ultrasound image by using phase change phantom, indicating that phantom with different internal shapes could be well designed using this strategy. In conclusion, the preparation strategy is feasible for pattern designable hydrogel phantom and can provide valuable prospects for ultrasound imaging.

As a rapidly maturing class of many-core parallel computing hardware, graphical processing unit (GPU) has enjoyed a surge of interest in the medical ultrasound community in the past decade. In particular, the software-level programmability of GPUs has significantly lowered the entry barrier for ultrasound imaging researchers (who might not be parallel computing specialists) to pursue fast realization of novel imaging algorithms that have known theoretical potential but have yet to demonstrate their real-time feasibility. This presentation shall highlight how GPUs have emerged as a new computing workhorse in realizing various ultrasound imaging innovations. Of particular note is the enabling role that GPUs have played in fostering practical pursuit of high-frame-rate ultrasound (HiFRUS) imaging innovations that are based on direct processing of pre-beamformed radiofrequency (RF) data acquired from individual array elements. Using the state-of-art GPU technology, it is readily possible to achieve >1,000 fps HiFRUS beamforming throughput. GPU can also play a pivotal role in facilitating fast realization of computationally intensive HiFRUS algorithms, such as adaptive beamforming, color-encoded flow speckle imaging, and eigen-processing. The real-time performance of these GPU computing kernels will be discussed, and their practical implementation on software-oriented open-platform research systems will be presented.

In this paper, we propose a robust beamforming (BF) scheme for an integrated satellite and high altitude platform network, where a multibeam satellite system shares the millimeter wave spectrum with a high altitude platform system. Specifically, we first exploit the weighted Tchebycheff method and formulate a multi-objective optimization problem to obtain the Pareto optimal trade-off between two conflicting yet desirable objectives, namely, sum rate maximization and total transmit power minimization, while satisfying the quality-of-service constraints of both earth stations and mobile terminals and per-antenna transmit power budget. Then, by using the angular information based imperfect channel state information, we propose a low-complexity discretization method to transform the non-convex objective function and constraints to the convex ones. Furthermore, a monotonic optimization scheme combined with iterative penalty function algorithm is presented to obtain the BF weight vectors with low computational complexity and fast convergence rate. Finally, numerical results are provided to confirm the effectiveness and superiority of the proposed approach in comparison to the existing related works.

A novel adaptive beamforming (BF) receiver is proposed for a multiple-input–multiple-output communication system over multipath fading channels. By dividing a large number of receive antennas into many adaptive beamformers (ABFs), the proposed system reduces the array dimension in order to simplify the signal detection process and enjoys the benefit of BF techniques to improve the symbol-error-rate (SER) performance. The effectiveness of the proposed system depends on the number of ABFs and the number of antennas per ABF. The statistical properties of complex Wishart matrices are applied to analyse the SER performance of the proposed system with both maximum-likelihood (ML) detection and zero-forcing detection. Furthermore, the authors have derived an upper bound for SER of the ML detection based on the smallest eigenvalue distribution. Through the authors analysis, it has been shown that the proposed system using ML detection provides comparable SER performance, but with a lower complexity as compared with that of a conventional ML receiver because of reduced array dimensions.

We propose an adaptive transmit and receive beam forming (TRBF) scheme for Time Division Duplex Multiple Input and Multiple Output (TDD-MIMO) system. Through analyzing the anti-jamming mechanism and deficiency from the point of subspace projection, we solve the optimization problem of designing TRBF and give an adaptive scheme. Firstly, the receiver determines receive beam former according to the legitimate channel matrix and interference null space. Secondly, the receiver uses the receive beam former as the transmit beam former to send training sequences to the transmitter for estimating the receive space. Finally, the transmitter determines the transmit beam former to correct the transmit power pointing to the receive space for avoiding power leakage. Since all of the transmit power reaches receiver and is collected, the receiver can get the maximum signal-to interference plus noise ratios (SINR). Simulation results show that the proposed method outperforms conventional beam forming significantly and has a similar performance to the theoretical value in the presence of repressive and deceptive interference.

Digital adaptive beamforming (ABF), with its ability to enhance frequency reuse and co-channel-interference rejection for improved service capacity and link quality, is expected to play an important role in future wireless communications. However, the performance of such a digital communication system strongly relies on the accuracy of synchronization. This paper investigates the system performance of digital adaptive beamforming in a digital QAM receiver in the presence of synchronization errors. The simulation results show that digital adaptive beamforming can cancel interference while simultaneously compensate for the carrier phase and frequency offset to support a reliable 64-QAM link. However, this system is very sensitive to the symbol timing error and the sampling timing offset. The system employing both ABF and adaptive equalization, which can reject interference in a multipath environment, is able to compensate for the symbol timing error and the sampling timing offset. The tracking range of the carrier frequency offset is also improved in the system with both adaptive beamforming and equalization.