Implementing capon beamforming on a GPU for real-time cardiac ultrasound imaging

Multi-apodization with cross-correlation combined with generalized sidelobe canceller applied to ultrasound imaging

BACKGROUND

Beamforming is vital for medical ultrasound imaging systems. The generalized sidelobe canceller (GSC) beamforming can improve the image quality of lateral resolution, but its performance improvement in contrast and robustness is limited.

OBJECTIVE

This paper proposes an improved generalized sidelobe canceller algorithm based on multi-apodization with cross-correlation (MAXB-IGSC), which aims to improve the contrast and robustness of ultrasound imaging while maintaining the high image resolution and background speckle quality of GSC.

METHODS

The proposed MAXB-IGSC uses multiple pairs of complementary received apodization functions to process the echo data individually to obtain multiple pairs of data sets. The average of their normalized cross-correlation coefficients is then calculated and utilized to determine the adaptive subarray length of the GSC covariance matrix and weights the output of the improved GSC.

RESULTS

The MAXB-IGSC improves the contrast ratio (CR) by 171.18% in anechoic cyst simulation and by 91.23%/130.97%/171.76% in geabr_0 (a dataset from the University of Michigan) experiment compared with GSC, respectively. Furthermore, MAXB-IGSC exhibits significant noise immunity, which greatly improves the robustness of the imaging. The technology also maintains the brightness and uniformity of the background speckle.

CONCLUSION

The proposed MAXB-IGSC has potential for obtaining high-quality ultrasound images in clinical applications.

Improved Ultrafast Power Doppler Imaging Using United Spatial-Angular Adaptive Scaling Wiener Postfilter

Ultrafast power Doppler imaging (uPDI) using high-frame-rate plane-wave transmission is a new microvascular imaging modality that offers high Doppler sensitivity. However, due to the unfocused transmission of plane waves, the echo signal is subject to interference from noise and clutter, resulting in a low signal-to-noise ratio (SNR) and poor image quality. Adaptive beamforming techniques are effective in suppressing noise and clutter for improved image quality. In this study, an adaptive beamformer based on a united spatial-angular adaptive scaling Wiener (uSA-ASW) postfilter is proposed to improve the resolution and contrast of uPDI. In the proposed method, the signal power and noise power of the Wiener postfilter are estimated by uniting spatial and angular signals, and a united generalized coherence factor (uGCF) is introduced to dynamically adjust the noise power estimation and enhance the robustness of the method. Simulation and in vivo data were used to verify the effectiveness of the proposed method. The results show that the uSA-ASW can achieve higher resolution and significant improvements in image contrast and background noise suppression compared with conventional delay-and-sum (DAS), coherence factor (CF), spatial-angular CF (SACF), and adaptive scaling Wiener (ASW) postfilter methods. In the simulations, uSA-ASW improves contrast-to-noise ratio (CNR) by 34.7 dB (117.3%) compared with DAS, while reducing background noise power (BNP) by 52 dB (221.4%). The uSA-ASW method provides full-width at half-maximum (FWHM) reductions of [Formula: see text] (59.5%) and [Formula: see text] (56.9%), CNR improvements of 25.6 dB (199.9%) and 42 dB (253%), and BNP reductions of 46.1 dB (319.3%) and 12.9 dB (289.1%) over DAS in the experiments of contrast-free human neonatal brain and contrast-free human liver, respectively. In the contrast-free experiments, uSA-ASW effectively balances the performance of noise and clutter suppression and enhanced microvascular visualization. Overall, the proposed method has the potential to become a reliable microvascular imaging technique for aiding in more accurate diagnosis and detection of vascular-related diseases in clinical contexts.

Low complexity adaptive ultrasound image beamformer combined with improved multiphase apodization with cross-correlation

In this paper, an ultrasound imaging method combined with low-complexity adaptive beamformer (LCA) and improved multiphase apodization with cross-correlation (IMPAX) is proposed to improve image resolution and contrast with low hardware cost. Firstly, the delayed echo signal is apodized by the LCA to obtain a narrow mainlobe width echo signal and LCA output. Then, multiple pairs of complementary square-wave phase apodizations are applied to the apodized echo signal to obtain corresponding signal pairs, which are used to calculate the normalized cross-correlation (NCC) matrix. Finally, the average value of the NCC matrices is filtered by 2-D means, and the filtered result is introduced as the weighting factor for the LCA output. The simulation and experimental results show that the proposed LCA-IMPAX can effectively reduce the mainlobe width, suppress clutter, and be robust to noise. Compared with DAS, LCA, and MPAX, for simulated point targets, the full-width at half-maximum (FWHM, -6dB) of LCA-IMPAX is reduced by 49.22%, 10.06%, and 48.67%, respectively. For simulated cyst, the CR is improved by 219.91%, 138.08%, and 103.44%, respectively. For experimental cysts, the CR is improved by an average of 145.00%, 136.14%, and 55.09%, respectively. The results of human heart data indicate that LCA-IMPAX has good imaging quality in vivo. Since the proposed method does not involve covariance matrix inversion, it can be applied in real-time imaging systems.

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.

An analytical study of spatial resolution enhancement for a dual-frequency acoustic beamformer

In this paper, we address an acoustic directed-self-assembly (DSA) problem for aiming to pattern particles based on creating an appropriate acoustic field by the fine adjustment of transducer operating parameters. The proposed idea is to incorporate the DSA problem with multi-frequency beamforming techniques. First, the boundary element method (BEM) is implemented for the direct modeling of the proposed DSA problem. Then, it is integrated with the concept of dual-frequency beamforming. In this study, the influence of changing excitation frequency is investigated on the spatial resolution enhancement of the pressure field. Also, the optimal frequency difference is calculated theoretically to produce two adjacent pressure traps with maximum separability and, therefore, maximum spatial resolution in a two-frequency acoustic beamformer without any restriction on the chamber shape. The performance of the proposed Dual-Frequency Beamforming (DFB) method is evaluated by simulations based on the finite element method (FEM) and compared with conventional Delay-And-Sum (DAS), Eigen Vector-Based (EigVec-based), and Bessel Beam techniques. Several evaluation metrics such as Full Width at Half Maximum (FWHM), Peak Side-lobe Level (PSL), Contrast Ratio (CR), Positioning Accuracy (PA), and processing time are considered for comparisons. Simulation results indicate the superiority of the proposed DFB method over the mentioned methods in separability and focusing precision when the two pressure traps are close to each other.

Accelerated 2-D Real-Time Refraction-Corrected Transcranial Ultrasound Imaging

In a recent study, we proposed a technique to correct aberration caused by the skull and reconstruct a transcranial B-mode image with a refraction-corrected synthetic aperture imaging (SAI) scheme. Given a sound speed map, the arrival times were calculated using a fast marching technique (FMT), which solves the Eikonal equation and, therefore, is computationally expensive for real-time imaging. In this article, we introduce a two-point ray tracing method, based on Fermat's principle, for fast calculation of the travel times in the presence of a layered aberrator in front of the ultrasound probe. The ray tracing method along with the reconstruction technique is implemented on a graphical processing unite (GPU). The point spread function (PSF) in a wire phantom image reconstructed with the FMT and the GPU implementation was studied with numerical synthetic data and experiments with a bone-mimicking plate and a sagittally cut human skull. The numerical analysis showed that the error on travel times is less than 10% of the ultrasound temporal period at 2.5 MHz. As a result, the lateral resolution was not significantly degraded compared with images reconstructed with FMT-calculated travel times. The results using the synthetic, bone-mimicking plate, and skull dataset showed that the GPU implementation causes a lateral/axial localization error of 0.10/0.20, 0.15/0.13, and 0.26/0.32 mm compared with a reference measurement (no aberrator in front of the ultrasound probe), respectively. For an imaging depth of 70 mm, the proposed GPU implementation allows reconstructing 19 frames/s with full synthetic aperture (96 transmission events) and 32 frames/s with multiangle plane wave imaging schemes (with 11 steering angles) for a pixel size of [Formula: see text]. Finally, refraction-corrected power Doppler imaging is demonstrated with a string phantom and a bone-mimicking plate placed between the probe and the moving string. The proposed approach achieves a suitable frame rate for clinical scanning while maintaining the image quality.

Minimum variance beamforming combined with covariance matrix-based adaptive weighting for medical ultrasound imaging

BACKGROUND

The minimum variance (MV) beamformer can significantly improve the image resolution in ultrasound imaging, but it has limited performance in noise reduction. We recently proposed the covariance matrix-based statistical beamforming (CMSB) for medical ultrasound imaging to reduce sidelobes and incoherent clutter.

METHODS

In this paper, we aim to improve the imaging performance of the MV beamformer by introducing a new pixel-based adaptive weighting approach based on CMSB, which is named as covariance matrix-based adaptive weighting (CMSAW). The proposed CMSAW estimates the mean-to-standard-deviation ratio (MSR) of a modified covariance matrix reconstructed by adaptive spatial smoothing, rotary averaging, and diagonal reducing. Moreover, adaptive diagonal reducing based on the aperture coherence is introduced in CMSAW to enhance the performance in speckle preservation.

RESULTS

The proposed CMSAW-weighted MV (CMSAW-MV) was validated through simulation, phantom experiments, and in vivo studies. The phantom experimental results show that CMSAW-MV obtains resolution improvement of 21.3% and simultaneously achieves average improvements of 96.4% and 71.8% in average contrast and generalized contrast-to-noise ratio (gCNR) for anechoic cyst, respectively, compared with MV. in vivo studies indicate that CMSAW-MV improves the noise reduction performance of MV beamformer.

CONCLUSION

Simulation, experimental, and in vivo results all show that CMSAW-MV can improve resolution and suppress sidelobes and incoherent clutter and noise. These results demonstrate the effectiveness of CMSAW in improving the imaging performance of MV beamformer. Moreover, the proposed CMSAW with a computational complexity of [Formula: see text] has the potential to be implemented in real time using the graphics processing unit.

Design and Implementation of a Modular and Scalable Research Platform for Ultrasound Computed Tomography

Increasing attention has been attracted to the research of ultrasound computed tomography (USCT). This article reports the design considerations and implementation details of a novel USCT research system named UltraLucid, which aims to provide a user-friendly platform for researchers to develop new algorithms and conduct clinical trials. The modular design strategy is adopted to make the system highly scalable. A prototype has been assembled in our laboratory, which is equipped with a 2048-element ring transducer, 1024 transmit (TX) channels, 1024 receive (RX) channels, two servers, and a control unit. The prototype can acquire raw data from 1024 channels simultaneously using a modular data acquisition and a transfer system, consisting of 16 excitation and data acquisition (EDAQ) boards. Each EDAQ board has 64 independent TX and RX channels and 4-Gb Ethernet interfaces for raw data transmission. The raw data can be transferred to two servers at a theoretical rate of 64 Gb/s. Both servers are equipped with a 10.9-TB solid-state drive (SSD) array that can store raw data for offline processing. Alternatively, after processing by onboard field-programmable gate arrays (FPGAs), the raw data can be processed online using multicore central processing units (CPUs) and graphics processing units (GPUs) in each server. Through control software running on the host computer, the researchers can configure parameters for transmission, reception, and data acquisition. Novel TX-RX scheme and coded imaging can be implemented. The modular hardware structure and the software-based processing strategy make the system highly scalable and flexible. The system performance is evaluated with phantoms and in vivo experiments.

A Real-Time, GPU-Based Implementation of Aperture Domain Model Image REconstruction

Multipath and off-axis scattering are two of the primary mechanisms for ultrasound image degradation. To address their impact, we have proposed Aperture Domain Model Image REconstruction (ADMIRE). This algorithm utilizes a model-based approach in order to identify and suppress sources of acoustic clutter. The ability of ADMIRE to suppress clutter and improve image quality has been demonstrated in previous works, but its use for real-time imaging has been infeasible due to its significant computational requirements. However, in recent years, the use of graphics processing units (GPUs) for general-purpose computing has enabled the significant acceleration of compute-intensive algorithms. This is because many modern GPUs have thousands of computational cores that can be utilized to perform massively parallel processing. Therefore, in this work, we have developed a GPU-based implementation of ADMIRE. The implementation on a single GPU provides a speedup of two orders of magnitude when compared to a serial CPU implementation, and additional speedup is achieved when the computations are distributed across two GPUs. In addition, we demonstrate the feasibility of the GPU implementation to be used for real-time imaging by interfacing it with a Verasonics Vantage 128 ultrasound research system. Moreover, we show that other beamforming techniques, such as delay-and-sum (DAS) and short-lag spatial coherence (SLSC), can be computed and simultaneously displayed with ADMIRE. The frame rate depends upon various parameters, and this is exhibited in the multiple imaging cases that are presented. An open-source code repository containing CPU and GPU implementations of ADMIRE is also provided.

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.

Joint Generalized Coherence Factor and Minimum Variance Beamformer for Synthetic Aperture Ultrasound Imaging

The delay-and-sum (DAS) beamformer is the most commonly used method in medical ultrasound imaging. Compared with the DAS beamformer, the minimum variance (MV) beamformer has an excellent ability to improve lateral resolution by minimizing the output of interference and noise power. However, it is hard to overcome the tradeoff between satisfactory lateral resolution and speckle preservation performance due to the fixed subarray length of covariance matrix estimation. In this study, a new approach for MV beamforming with adaptive spatial smoothing is developed to address this problem. In the new approach, the generalized coherence factor (GCF) is used as a local coherence detection tool to adaptively determine the subarray length for spatial smoothing, which is called adaptive spatial-smoothed MV (AMV). Furthermore, another adaptive regional weighting strategy based on the local signal-to-noise ratio (SNR) and GCF is devised for AMV to enhance the image contrast, which is called GCF regional weighted AMV (GAMV). To evaluate the performance of the proposed methods, we compare them with the standard MV by conducting the simulation, in vitro experiment, and the in vivo rat mammary tumor study. The results show that the proposed methods outperform MV in speckle preservation without an appreciable loss in lateral resolution. Moreover, GAMV offers excellent performance in image contrast. In particular, AMV can achieve maximal improvements of speckle signal-to-noise ratio (SNR) by 96.19% (simulation) and 62.82% (in vitro) compared with MV. GAMV achieves improvements of contrast-to-noise ratio by 27.16% (simulation) and 47.47% (in vitro) compared with GCF. Meanwhile, the losses in lateral resolution of AMV are 0.01 mm (simulation) and 0.17 mm (in vitro) compared with MV. Overall, this indicates that the proposed methods can effectively address the inherent limitation of the standard MV in order to improve the image quality.

High Resolution, High Contrast Beamformer Using Minimum Variance and Plane Wave Nonlinear Compounding with Low Complexity

The plane wave compounding (PWC) is a promising modality to improve the imaging quality and maintain the high frame rate for ultrafast ultrasound imaging. In this paper, a novel beamforming method is proposed to achieve higher resolution and contrast with low complexity. A minimum variance (MV) weight calculated by the partial generalized sidelobe canceler is adopted to beamform the receiving array signals. The dimension reduction technique is introduced to project the data into lower dimensional space, which also contributes to a large subarray length. Estimation of multi-wave receiving covariance matrix is performed and then utilized to determine only one weight. Afterwards, a fast second-order reformulation of the delay multiply and sum (DMAS) is developed as nonlinear compounding to composite the beamforming output of multiple transmissions. Simulations, phantom, in vivo, and robustness experiments were carried out to evaluate the performance of the proposed method. Compared with the delay and sum (DAS) beamformer, the proposed method achieved 86.3% narrower main lobe width and 112% higher contrast ratio in simulations. The robustness to the channel noise of the proposed method is effectively enhanced at the same time. Furthermore, it maintains a linear computational complexity, which means that it has the potential to be implemented for real-time response.

Advances in ultrasonography: image formation and quality assessment

Delay-and-sum (DAS) beamforming is widely used for generation of B-mode images from echo signals obtained with an array probe composed of transducer elements. However, the resolution and contrast achieved with DAS beamforming are determined by the physical specifications of the array, e.g., size and pitch of elements. To overcome this limitation, adaptive imaging methods have recently been explored extensively thanks to the dissemination of digital and programmable ultrasound systems. On the other hand, it is also important to evaluate the performance of such adaptive imaging methods quantitatively to validate whether the modification of the image characteristics resulting from the developed method is appropriate. Since many adaptive imaging methods have been developed and they often alter image characteristics, attempts have also been made to update the methods for quantitative assessment of image quality. This article provides a review of recent developments in adaptive imaging and image quality assessment.

Multi-Operator Minimum Variance Adaptive Beamforming Algorithms Accelerated With GPU

The goal of this work is to design high-resolution, high-contrast and robust MV adaptive beamforming algorithms, which are also implemented in real-time frame rate. Multi-operator optimization is introduced into MV adaptive beamforming in this work to propose a multi-operator MV adaptive beamforming algorithmic optimization framework. Based on the proposed algorithmic optimization framework, the algorithm optimization can be either conducted by activating a single optimization operator, or conducted by activating multiple optimization operators. The multi-operator MV (MOMV) adaptive beamforming algorithms are then derived from this framework. Moreover, in order to promote the real-time imaging capability of MOMV beamforming, a GPU-based parallel acceleration framework is proposed along with the algorithmic optimization framework by exploring the image-level coarse-grained parallelization and pixel-level fine-grained parallelization. GPU computing resource allocation strategy and memory access strategy are both explored to better design the acceleration framework. Comprehensive quantitative simulation evaluations and qualitative in vivo experiments of imaging performance are studied, and the results demonstrate that the proposed MOMV adaptive beamforming algorithms significantly improve the imaging performance as compared with other MV beamforming algorithms, which have high resolution, high contrast, good robustness, and real-time imaging capability with thousands of acceleration speedup. Furthermore, the MOMV beamforming algorithm without eigen-decomposition and projection optimization operator achieves much higher beamforming frame rate with little downgrade of image quality as compared with the MOMV beamforming algorithm with all optimization operators.

Real time SVD-based clutter filtering using randomized singular value decomposition and spatial downsampling for micro-vessel imaging on a Verasonics ultrasound system

Singular value decomposition (SVD)-based clutter filters can robustly reject the tissue clutter as compared with the conventional high pass filter-based clutter filters. However, the computational burden of SVD makes real time SVD-based clutter filtering challenging (e.g. frame rate at least 10-15 Hz with region of interest of about 4 × 4 cm²). Recently, we proposed an acceleration method based on randomized SVD (rSVD) clutter filtering and randomized spatial downsampling, which can significantly reduce the computational complexity without compromising the clutter rejection capability. However, this method has not been implemented on an ultrasound scanner and tested for its performance. In this study, we implement this acceleration method on a Verasonics scanner using a multi-core CPU architecture, and evaluate the selections of the imaging and processing parameters to enable real time micro-vessel imaging. The Blood-to-Clutter Ratio (BCR) performance was evaluated on a Verasonics machine with different settings of parameters such as block size and ensemble size. The demonstration of real time process was implemented on a 12-core CPU (downsampling factor of 12, 12-threads in this study) host computer. The processing time of the rSVD-based clutter filter was less than 30 ms and BCRs were higher than 20 dB as the block size, ensemble size and the rank of tissue clutter subspace were set as 30 × 30, 45 and 26 respectively. We also demonstrate that the micro-vessel imaging frame rate of the proposed architecture can reach approximately 22 Hz when the block size, ensemble size and the rank of tissue clutter subspace were set as 20 × 20 pixels, 45 and 26 respectively (using both images and supplementary videos). The proposed method may be important for real time 2D scanning of tumor microvessels in 3D to select and store the most representative 2D view with most abnormal micro-vessels for better diagnosis.

Converting Coherence to Signal-to-noise Ratio for Enhancement of Adaptive Ultrasound Imaging

High-frame-rate ultrasound is an emerging technique for functional ultrasound imaging. However, the lateral spatial resolution and contrast in high-frame-rate ultrasound with an unfocused transmit beam are inherently lower than those in conventional ultrasonic imaging based on the line-by-line acquisition using a focused ultrasonic beam because of the low directivity of the transmit beam. Coherence-based beamforming methods were introduced in ultrasound imaging for improvement of image quality. Such methods improve the lateral spatial resolution using the coherence among ultrasonic echo signals received by individual transducer elements. In this study, a new method based on the signal-to-noise ratio (SNR) among the element echo signals was developed for enhancement of the effect of the coherence factor (CF), which was previously developed for improvement in spatial resolution and contrast. In the proposed method, a new factor, namely, SNR factor, was introduced, and the relationship between the previously developed CF and SNR factor was discussed. The proposed method was implemented in plane wave imaging, and the performance was evaluated by simulated and phantom experiments. In simulation, the lateral spatial resolution and contrast obtained with the conventional CF were 0.23 mm and 47.0 dB, respectively, which were significantly better than 0.39 mm and 15.3 dB obtained by conventional delay-and-sum (DAS) beamforming. Using the proposed method, the lateral spatial resolution and contrast were further improved to 0.12 mm and 69.8 dB, respectively. Similar trends were found also in phantom experiments.

A dynamic generalized coherence factor for side lobe suppression in ultrasound imaging

Coherence-based weighting techniques have been widely studied to weight beamsummed data to improve image quality in ultrasound imaging. Although generalized coherence factor (GCF) enhances the robustness of coherence factor (CF) with preserved speckle pattern by including some incoherent components, the side lobe suppression performance is insufficient due to constant cut-off frequency M₀. To address this problem, we introduced in this paper a dynamic GCF method, referred to as DGCF-C, based on the amplitude standard deviation and the convolution output of aperture data. The cut-off frequency is adaptively selected for GCF at each imaging point using the amplitude standard deviation of aperture data. Moreover, the convolution output of aperture data is used to calculate the dynamic GCF. The proposed method is evaluated in simulation and tissue-mimicking phantom studies. The image quality was analyzed in terms of resolution, contrast ratio (CR), generalized contrast-to-noise ratio (GCNR), speckle signal-to-noise ratio (sSNR), and signal-to-noise ratio (SNR). The results demonstrate that DGCF-C (M_max=2) achieves mean resolution improvements of 35.1% in simulation, and 32.6% in experiment, compared with GCF (M₀=1). Moreover, DGCF-C (M_max=4) outperforms GCF (M₀=2) with an average GCNR improvement of 13.5% and an average sSNR improvement of 15.2%, which indicates the better-preservation of speckle.

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.

A novel adaptive apodization to improve the resolution of phased subarray imaging in medical ultrasound

PURPOSE

Phased subarray imaging (PSA) was previously proposed to extend the receive aperture length. Using overlapped subarrays as transmitters in PSA leads to decrement of sidelobe levels of the overall beam compared to full phased array imaging (PHA). This paper proposes an adaptive compounding of subarray images in PSA to improve both the resolution and contrast compared with PHA.

METHOD

Adaptive apodization (ADAP) is defined proportional to the beamformed responses of subarrays such that the overall energy after compounding is minimized.

RESULTS

The simulation and experimental results validate the performance of applying ADAP in PSA. The full width at half maximum (FWHM) at a depth of 30 mm in the proposed PSA is about 0.2 mm, compared to a FWHM of 0.6 mm with PHA imaging. Measuring the contrast ratio index shows that the ADAP method also improves the contrast in PSA imaging at least 25% compared to PHA imaging.

CONCLUSION

Applying the proposed ADAP, besides conventional compounding in PSA imaging, leads to improvement of both the resolution and contrast compared to PHA imaging.

Wireless, Real-Time Plane-Wave Coherent Compounding on an iPhone: A Feasibility Study

The processing power in commercially available hand-held devices has improved dramatically in recent years. In parallel, techniques used in high-frame-rate medical ultrasound imaging, especially plane-wave (PW) imaging, have reduced the number of ultrasound transmissions and amount of data necessary to reconstruct an ultrasound image. In combination, the processing power and data reduction allow all of the processing steps in ultrasound image formation, from raw ultrasound channel data to final rendering, to be performed on a hand-held device. In this study, we send the raw ultrasound channel data from a research scanner wirelessly to an off-the-shelf hand-held device. The hand-held unit's graphical processing unit is processing the raw ultrasound data into the final image, achieving real-time frame rates on the order of 60-90 frames per second (FPS) for a single-angle PW transmission. Higher quality images are achieved by trading off frame rate by coherently compounding multiple PW images, resulting in frame rates on the order of, e.g., 13 FPS when coherently compounding 7 PW transmissions. The presented setup has the potential of providing image quality which could be valuable for simple medical ultrasound diagnostic scans of, e.g., the carotid artery or thyroid. Also, since the computationally expensive beamforming can be done in off-the-shelf devices, this could reduce the price of hand-held ultrasound systems in the future.

Improved Visualization in Difficult-to-Image Stress Echocardiography Patients Using Real-Time Harmonic Spatial Coherence Imaging

Stress echocardiography is used to detect myocardial ischemia by evaluating cardiovascular function both at rest and at elevated heart rates. Stress echocardiography requires excellent visualization of the left ventricle (LV) throughout the cardiac cycle. However, LV endocardial border visualization is often negatively impacted by high levels of clutter associated with patient obesity, which has risen dramatically worldwide in recent decades. Short-lag spatial coherence (SLSC) imaging has demonstrated reduced clutter in several applications. In this work, a computationally efficient formulation of SLSC was implemented into an object-oriented graphics processing unit-based software beamformer, enabling real-time (>30 frames per second) SLSC echocardiography on a research ultrasound scanner. The system was then used to image 15 difficult-to-image stress echocardiography patients in a comparison study of tissue harmonic imaging (THI) and harmonic spatial coherence imaging (HSCI). Video clips of four standard stress echocardiography views acquired with either THI or HSCI were provided in random shuffled order to three experienced readers. Each reader rated the visibility of 17 LV segments as "invisible," "suboptimally visualized," or "well visualized," with the first two categories indicating a need for contrast agent. In a symmetry test unadjusted for patientwise clustering, HSCI demonstrated a clear superiority over THI ( ). When measured on a per-patient basis, the median total score significantly favored HSCI with . When collapsing the ratings to a two-level scale ("needs contrast" versus "well visualized"), HSCI once again showed an overall superiority over THI, with by McNemar test adjusted for clustering.

Resolving Ultrasound Contrast Microbubbles Using Minimum Variance Beamforming

Minimum Variance (MV) beamforming is known to improve the lateral resolution of ultrasound images and enhance the separation of isolated point scatterers. This paper aims to evaluate the adaptive beamformer's performance with flowing microbubbles (MBs) which are relevant to super-resolution ultrasound imaging. Simulations using point scatterer data from single emissions were complemented by an experimental investigation performed using a capillary tube phantom and the Synthetic Aperture Real-time Ultrasound System (SARUS). The MV performance was assessed by the minimum distance that allows the display of two scatterers positioned side-by-side, the lateral Full-Width-at-Half-Maximum (FWHM), and the Peak-Sidelobe-Level (PSL). In the tube, scatterer responses separated by down to [Formula: see text] (or 1.05λ ) were distinguished by the MV method, while the standard Delay-And-Sum (DAS) beamformers were unable to achieve such separation. Up to ninefold FWHM decrease was also measured in favor of the MV beamformer for individual echoes from MBs. The lateral distance between two scatterers impacted on their FWHM value, and additional differences in the scatterers' axial or out-of-plane position also impacted on their size and appearance. The simulation and experimental results were in agreement in terms of lateral resolution. The point scatterer study showed that the proposed MV imaging scheme provided clear resolution benefits compared to DAS. Current super-resolution methods mainly depend on DAS beamformers. Instead, the use of the MV method may provide a larger number of detected, and potentially better localized, MB scatterers.

2-D Minimum Variance Based Plane Wave Compounding with Generalized Coherence Factor in Ultrafast Ultrasound Imaging

Plane wave compounding (PWC) is an effective modality for ultrafast ultrasound imaging. It can provide higher resolution and better noise reduction than plane wave imaging (PWI). In this paper, a novel beamformer integrating the two-dimensional (2-D) minimum variance (MV) with the generalized coherence factor (GCF) is proposed to maintain the high resolution and contrast along with a high frame rate for PWC. To specify, MV beamforming is adopted in both the transmitting aperture and the receiving one. The subarray technique is therefore upgraded into the sub-matrix division. Then, the output of each submatrix is used to adaptively compute the GCF using a 2-D fast Fourier transform (FFT). After the 2-D MV beamforming and the 2-D GCF weighting, the final output can be obtained. Results of simulations, phantom experiments, and in vivo studies confirm the advantages of the proposed method. Compared with the delay-and-sum (DAS) beamformer, the full width at half maximum (FWHM) is 90% smaller and the contrast ratio (CR) improvement is 154% in simulations. The over-suppression of desired signals, which is a typical drawback of the coherence factor (CF), can be effectively avoided. The robustness against sound velocity errors is also enhanced.

An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor

The beamforming performance has a large impact on image quality in ultrasound imaging. Previously, several adaptive weighting factors including coherence factor (CF) and generalized coherence factor (GCF) have been proposed to improved image resolution and contrast. In this paper, we propose a new adaptive weighting factor for ultrasound imaging, which is called signal mean-to-standard-deviation factor (SMSF). SMSF is defined as the mean-to-standard-deviation of the aperture data and is used to weight the output of delay-and-sum (DAS) beamformer before image formation. Moreover, we develop a robust SMSF (RSMSF) by extending the SMSF to the spatial frequency domain using an altered spectrum of the aperture data. In addition, a square neighborhood average is applied on the RSMSF to offer a more smoothed square neighborhood RSMSF (SN-RSMSF) value. We compared our methods with DAS, CF, and GCF using simulated and experimental synthetic aperture data sets. The quantitative results show that SMSF results in an 82% lower full width at half-maximum (FWHM) but a 12% lower contrast ratio (CR) compared with CF. Moreover, the SN-RSMSF leads to 15% and 10% improvement, on average, in FWHM and CR compared with GCF while maintaining the speckle quality. This demonstrates that the proposed methods can effectively improve the image resolution and contrast.

Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging

Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L³) to O(L²).

GPU-based Green's function simulations of shear waves generated by an applied acoustic radiation force in elastic and viscoelastic models

Shear wave calculations induced by an acoustic radiation force are very time-consuming on desktop computers, and high-performance graphics processing units (GPUs) achieve dramatic reductions in the computation time for these simulations. The acoustic radiation force is calculated using the fast near field method and the angular spectrum approach, and then the shear waves are calculated in parallel with Green's functions on a GPU. This combination enables rapid evaluation of shear waves for push beams with different spatial samplings and for apertures with different f/#. Relative to shear wave simulations that evaluate the same algorithm on an Intel i7 desktop computer, a high performance nVidia GPU reduces the time required for these calculations by a factor of 45 and 700 when applied to elastic and viscoelastic shear wave simulation models, respectively. These GPU-accelerated simulations also compared to measurements in different viscoelastic phantoms, and the results are similar. For parametric evaluations and for comparisons with measured shear wave data, shear wave simulations with the Green's function approach are ideally suited for high-performance GPUs.

An efficient subarray average delay multiply and sum beamformer algorithm in ultrasound imaging

Beamformer plays an important role in medical ultrasound imaging systems. The delay multiply and sum (DMAS) beamformer achieves better performance in contrast and resolution compared with the delay and sum (DAS) beamformer, but suffers from higher computational complexity and partial energy loss. The higher computational complexity mainly arises from the multiply and geometric average operation, which needs (N²-N)/2 computations at every point, where N denotes the number of array elements. The partial energy loss, mainly due to the autocorrelation component of the echo signals, has been neglected in the DMAS beamformer. In this paper, we propose a subarray average delay multiply and sum (SA-DMAS) beamformer which is combined with subarray average technique of covariance matrix and DMAS beamformer. This will lower the computational complexity, while keeping the side lobe suppressing property of DMAS. The main idea of the proposed method is adding autocorrelation component of the echo signals to DMAS, and converting the expression in covariance matrix form. The subarray average technique is used to estimate the covariance matrix of the echo signals. The field II simulation of point targets and cyst phantoms was used to prove the performance of the proposed method. An RF data experiment was applied to support the feasibility and validity of our method. The simulation and experimental results show that our method has a lower computational complexity as O(9/2L²) , where L denotes the sub-array size, and has equivalent performance like the MV and DMAS beamformer.

Passive acoustic mapping of cavitation using eigenspace-based robust Capon beamformer in ultrasound therapy

Pulse-echo imaging technique can only play a role when high intensity focused ultrasound (HIFU) is turned off due to the interference between the primary HIFU signal and the transmission pulse. Passive acoustic mapping (PAM) has been proposed as a tool for true real-time monitoring of HIFU therapy. However, the most-used PAM algorithm based on time exposure acoustic (TEA) limits the quality of cavitation image. Recently, robust Capon beamformer (RCB) has been used in PAM to provide improved resolution and reduced artifacts over TEA-based PAM, but the presented results have not been satisfactory. In the present study, we applied an eigenspace-based RCB (EISRCB) method to further improve the PAM image quality. The optimal weighting vector of the proposed method was found by projecting the RCB weighting vector onto the desired vector subspace constructed from the eigenstructure of the covariance matrix. The performance of the proposed PAM was validated by both simulations and in vitro histotripsy experiments. The results suggested that the proposed PAM significantly outperformed the conventionally used TEA and RCB-based PAM. The comparison results between pulse-echo images of the residual bubbles and cavitation images showed the potential of our proposed PAM in accurate localization of cavitation activity during HIFU therapy.

Hypothesis of Improved Visualization of Microstructures in the Interventricular Septum with Ultrasound and Adaptive Beamforming

In this work, in vivo ultrasound cardiac images created with Capon's minimum variance adaptive beamformer are compared with images acquired with the conventional delay-and-sum beamformer. Specifically, we provide three views of a human heart imaged through the parasternal short-axis, the parasternal long-axis and the apical four-chamber views. The minimum variance beamformer produced images with improved lateral resolution, resulting in better resolved speckle structure and improved edges, especially on close investigation of the interventricular septum. These improvements in image quality might possibly improve the visualization of microstructures in the human heart.

Experimental performance assessment of the sub-band minimum variance beamformer for ultrasound imaging

Recent progress in adaptive beamforming techniques for medical ultrasound has shown that current resolution limits can be surpassed. One method of obtaining improved lateral resolution is the Minimum Variance (MV) beamformer. The frequency domain implementation of this method effectively divides the broadband ultrasound signals into sub-bands (MVS) to conform with the narrow-band assumption of the original MV theory. This approach is investigated here using experimental Synthetic Aperture (SA) data from wire and cyst phantoms. A 7MHz linear array transducer is used with the SARUS experimental ultrasound scanner for the data acquisition. The lateral resolution and the contrast obtained, are evaluated and compared with those from the conventional Delay-and-Sum (DAS) beamformer and the MV temporal implementation (MVT). From the wire phantom the Full-Width-at-Half-Maximum (FWHM) measured at a depth of 52mm, is 16.7μm (0.08λ) for both MV methods, while the corresponding values for the DAS case are at least 24 times higher. The measured Peak-Side-lobe-Level (PSL) may reach -41dB using the MVS approach, while the values from the DAS and MVT beamforming are above -24dB and -33dB, respectively. From the cyst phantom, the power ratio (PR), the contrast-to-noise ratio (CNR), and the speckle signal-to-noise ratio (sSNR) measured at a depth of 30mm are at best similar for MVS and DAS, with values ranging between -29dB and -30dB, 1.94 and 2.05, and 2.16 and 2.27 respectively. In conclusion the MVS beamformer is not suitable for imaging continuous targets, and significant resolution gains were obtained only for isolated targets.

Short-lag Spatial Coherence Ultrasound Imaging with Adaptive Synthetic Transmit Aperture Focusing

The short-lag spatial coherence (SLSC) imaging has been demonstrated to be advantageous over the traditional B-mode ultrasound imaging. With focused scanning beams, the SLSC imaging has an excellent performance in clutter reduction and lesion detection, especially in the low signal-to-noise ratio (SNR) scenarios. The synthetic aperture (SA) imaging is an appropriate mode for the SLSC imaging as the dynamic transmit focusing could keep a good focusing quality at any depth. However, the SLSC image may still suffer a bad resolution performance when a low lag value is used in the coherence summation to ensure the contrast enhancement. In this paper, an adaptive synthetic transmit (Tx) aperture focusing strategy is proposed for the SLSC imaging with the SA mode. Based on the achievements of adaptive beamforming, a minimum variance beamformer is applied in the Tx aperture to realize adaptive focusing. Spatial coherence is then measured in the receive aperture to form the SLSC image. Simulation and experimental studies were conducted to evaluate the proposed method. Experiments showed that the proposed method not only improved the poor resolution of the original SLSC image but also enhanced the speckle performance, which led to increased contrast-to-noise ratio and speckle SNR values.

A Fast and Robust Beamspace Adaptive Beamformer for Medical Ultrasound Imaging

Minimum variance beamformer (MVB) increases the resolution and contrast of medical ultrasound imaging compared with nonadaptive beamformers. These advantages come at the expense of high computational complexity that prevents this adaptive beamformer to be applied in a real-time imaging system. A new beamspace (BS) based on discrete cosine transform is proposed in which the medical ultrasound signals can be represented with less dimensions compared with the standard BS. This is because of symmetric beampattern of the beams in the proposed BS compared with the asymmetric ones in the standard BS. This lets us decrease the dimensions of data to two, so a high complex algorithm, such as the MVB, can be applied faster in this BS. The results indicated that by keeping only two beams, the MVB in the proposed BS provides very similar resolution and also better contrast compared with the standard MVB (SMVB) with only 0.44% of needed flops. Also, this beamformer is more robust against sound speed estimation errors than the SMVB.

Combined phase screen aberration correction and minimum variance beamforming in medical ultrasound

In recent years, applying adaptive beamforming to ultrasound imaging improves image quality in terms of resolution and contrast. One of the best adaptive beamformers in this field is the minimum variance (MV) beamformer which presents better resolution and edge definition compared to the traditional delay-and-sum (DAS) beamformer. However, in real situations, sound-velocity inhomogeneities cause phase aberration which leads to ambiguity in targets' location and degradation in resolution. This effect is a fundamental obstacle to utilize advantages of MV beamformer, although, in aberrating medium MV beamformer results in better performance compared to DAS. In this paper, two different levels of phase screens have been applied to simulate aberrator layers located close to the transducer. Also, prior to beamforming process, a conventional correction technique based on phase screen model is used. Simulations are performed in majority resolution of MV which has the lowest robustness. The results demonstrate that applying this correction method can retrieve the efficiency of the MV beamformer. Moreover, the method improves the performance of the MV in both terms of resolution and contrast. As corrected MV achieved at least 22% improvement in sidelobe reduction and 24% increase in contrast to noise ratio (CNR) with respect to the DAS corrected data. Also, according to experimental dataset 17% enhancement in CNR is yielded by MV.

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this paper, we assess the existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4- and 20-fold in vivo with a downsample factor of 2.

Quantitative Frequency-Domain Passive Cavitation Imaging

Passive cavitation detection has been an instrumental technique for measuring cavitation dynamics, elucidating concomitant bioeffects, and guiding ultrasound therapies. Recently, techniques have been developed to create images of cavitation activity to provide investigators with a more complete set of information. These techniques use arrays to record and subsequently beamform received cavitation emissions, rather than processing emissions received on a single-element transducer. In this paper, the methods for performing frequency-domain delay, sum, and integrate passive imaging are outlined. The method can be applied to any passively acquired acoustic scattering or emissions, including cavitation emissions. To compare data across different systems, techniques for normalizing Fourier transformed data and converting the data to the acoustic energy received by the array are described. A discussion of hardware requirements and alternative imaging approaches is additionally outlined. Examples are provided in MATLAB.

Rapid short-pulse sequences enhance the spatiotemporal uniformity of acoustically driven microbubble activity during flow conditions

Despite the promise of microbubble-mediated focused ultrasound therapies, in vivo findings have revealed over-treated and under-treated regions distributed throughout the focal volume. This poor distribution cannot be improved by conventional pulse shapes and sequences, due to their limited ability to control acoustic cavitation dynamics within the ultrasonic focus. This paper describes the design of a rapid short-pulse (RaSP) sequence which is comprised of short pulses separated by μs off-time intervals. Improved acoustic cavitation distribution was based on the hypothesis that microbubbles can freely move during the pulse off-times. Flowing SonoVue^® microbubbles (flow velocity: 10 mm/s) were sonicated with a 0.5 MHz focused ultrasound transducer using RaSP sequences (peak-rarefactional pressures: 146-900 kPa, pulse repetition frequency: 1.25 kHz, and pulse lengths: 5-50 cycles). The distribution of cavitation activity was evaluated using passive acoustic mapping. RaSP sequences generated uniform distributions within the focus in contrast to long pulses (50 000 cycles) that produced non-uniform distributions. Fast microbubble destruction occurred for long pulses, whereas microbubble activity was sustained for longer durations for shorter pulses. High-speed microscopy revealed increased mobility in the direction of flow during RaSP sonication. In conclusion, RaSP sequences produced spatiotemporally uniform cavitation distributions and could result in efficient therapies by spreading cavitation throughout the treatment area.

Adaptive windowing in contrast-enhanced intravascular ultrasound imaging

Intravascular ultrasound (IVUS) is one of the most commonly-used interventional imaging techniques and has seen recent innovations which attempt to characterize the risk posed by atherosclerotic plaques. One such development is the use of microbubble contrast agents to image vasa vasorum, fine vessels which supply oxygen and nutrients to the walls of coronary arteries and typically have diameters less than 200μm. The degree of vasa vasorum neovascularization within plaques is positively correlated with plaque vulnerability. Having recently presented a prototype dual-frequency transducer for contrast agent-specific intravascular imaging, here we describe signal processing approaches based on minimum variance (MV) beamforming and the phase coherence factor (PCF) for improving the spatial resolution and contrast-to-tissue ratio (CTR) in IVUS imaging. These approaches are examined through simulations, phantom studies, ex vivo studies in porcine arteries, and in vivo studies in chicken embryos. In phantom studies, PCF processing improved CTR by a mean of 4.2dB, while combined MV and PCF processing improved spatial resolution by 41.7%. Improvements of 2.2dB in CTR and 37.2% in resolution were observed in vivo. Applying these processing strategies can enhance image quality in conventional B-mode IVUS or in contrast-enhanced IVUS, where signal-to-noise ratio is relatively low and resolution is at a premium.

Transform-Based Channel-Data Compression to Improve the Performance of a Real-Time GPU-Based Software Beamformer

Graphics processing unit (GPU)-based software beamforming has advantages over hardware-based beamforming of easier programmability and a faster design cycle, since complicated imaging algorithms can be efficiently programmed and modified. However, the need for a high data rate when transferring ultrasound radio-frequency (RF) data from the hardware front end to the software back end limits the real-time performance. Data compression methods can be applied to the hardware front end to mitigate the data transfer issue. Nevertheless, most decompression processes cannot be performed efficiently on a GPU, thus becoming another bottleneck of the real-time imaging. Moreover, lossless (or nearly lossless) compression is desirable to avoid image quality degradation. In a previous study, we proposed a real-time lossless compression-decompression algorithm and demonstrated that it can reduce the overall processing time because the reduction in data transfer time is greater than the computation time required for compression/decompression. This paper analyzes the lossless compression method in order to understand the factors limiting the compression efficiency. Based on the analytical results, a nearly lossless compression is proposed to further enhance the compression efficiency. The proposed method comprises a transformation coding method involving modified lossless compression that aims at suppressing amplitude data. The simulation results indicate that the compression ratio (CR) of the proposed approach can be enhanced from nearly 1.8 to 2.5, thus allowing a higher data acquisition rate at the front end. The spatial and contrast resolutions with and without compression were almost identical, and the process of decompressing the data of a single frame on a GPU took only several milliseconds. Moreover, the proposed method has been implemented in a 64-channel system that we built in-house to demonstrate the feasibility of the proposed algorithm in a real system. It was found that channel data from a 64-channel system can be transferred using the standard USB 3.0 interface in most practical imaging applications.

Low complex subspace minimum variance beamformer for medical ultrasound imaging

Minimum variance (MV) beamformer enhances the resolution and contrast in the medical ultrasound imaging at the expense of higher computational complexity with respect to the non-adaptive delay-and-sum beamformer. The major complexity arises from the estimation of the L×L array covariance matrix using spatial averaging, which is required to more accurate estimation of the covariance matrix of correlated signals, and inversion of it, which is required for calculating the MV weight vector which are as high as O(L(2)) and O(L(3)), respectively. Reducing the number of array elements decreases the computational complexity but degrades the imaging resolution. In this paper, we propose a subspace MV beamformer which preserves the advantages of the MV beamformer with lower complexity. The subspace MV neglects some rows of the array covariance matrix instead of reducing the array size. If we keep η rows of the array covariance matrix which leads to a thin non-square matrix, the weight vector of the subspace beamformer can be achieved in the same way as the MV obtains its weight vector with lower complexity as high as O(η(2)L). More calculations would be saved because an η×L covariance matrix must be estimated instead of a L×L. We simulated a wire targets phantom and a cyst phantom to evaluate the performance of the proposed beamformer. The results indicate that we can keep about 16 from 43 rows of the array covariance matrix which reduces the order of complexity to 14% while the image resolution is still comparable to that of the standard MV beamformer. We also applied the proposed method to an experimental RF data and showed that the subspace MV beamformer performs like the standard MV with lower computational complexity.

Subarray coherence based postfilter for eigenspace based minimum variance beamformer in ultrasound plane-wave imaging

This paper introduces a new beamformer, which combines the eigenspace based minimum variance (ESBMV) beamformer with a subarray coherence based postfilter (SCBP), for improving the quality of ultrasound plane-wave imaging. The ESBMV beamformer has been validated in improving the imaging contrast, but the difficulty in dividing the signal subspace limits the usage of it in the low signal-to-noise ratio (SNR) scenarios. Coherence factor (CF) based methods could optimize the output of a distortionless beamformer to reduce sidelobes, but the influence by the subarray decorrelation technique on the postfilter design has not attracted enough concern before. Accordingly, an ESBMV-SCBP beamformer was proposed in this paper, which used the coherence of the subarray signal to compute an SCBP to optimize the ESBMV results. Simulated and experimental data were used to evaluate the performance of the proposed method. The results showed that the ESBMV-SCBP method achieved an improved imaging quality compared with the ESBMV beamformer. In the simulation study, the contrast ratio (CR) for an anechoic cyst was improved by 9.88 dB and the contrast-to-noise ratio (CNR) was improved by 0.97 over the ESBMV. In the experimental study, the CR improvements for two anechoic cysts were 7.32 dB and 9.45 dB, while the CNRs were improved by 1.27 and 0.66, respectively. The ESBMV-SCBP also showed advantages over the ESBMV-Wiener beamformer in preserving a less grainy speckle, which is closer to that of distortionless beamformers and benefits the imaging contrast. With a relatively small extra computational load, the proposed method has potential to enhance the quality of the ultrasound plane-wave imaging.

Enhancing effect of phase coherence factor for improvement of spatial resolution in ultrasonic imaging

PURPOSE

Spatial resolution is one of the important factors that determines ultrasound image quality. In the present study, methods using the phase variance of ultrasonic echoes received by individual transducer elements have been examined for improvement of spatial resolution.

METHOD

An imaging method, i.e., phase coherence imaging, which uses the phase coherence factor (PCF) obtained from the phase variance of received ultrasonic echoes, was recently proposed. Spatial resolution is improved by weighting ultrasonic RF signals obtained by delay-and-sum (DAS) beam forming using PCF. In the present study, alternative PCFs, i.e., exponential PCF, harmonic PCF, and Gaussian PCF, have been proposed and examined for further improvement of spatial resolution.

RESULT

Spatial resolutions realized by the proposed PCFs were evaluated by an experiment using a phantom. The full widths at half maxima of the lateral profiles of an echo from a string phantom were 2.61 mm (DAS only), 1.46 mm (conventional PCF), and 0.48-0.62 mm (proposed PCFs).

CONCLUSION

The PCFs newly proposed in the present study showed better spatial resolutions than the conventional PCF. The proposed PCFs also realized better visualization of echoes from a diffuse scattering medium than the conventional PCF.

Effect of element directivity on adaptive beamforming applied to high-frame-rate ultrasound

High-frame-rate ultrasound is a promising technique for measurement and imaging of cardiovascular dynamics. In high-frame-rate ultrasonic imaging, unfocused ultrasonic beams are used in transmit and multiple focused receiving beams are created by parallel beamforming using the delay and sum (DAS) method. However, the spatial resolution and contrast are degraded compared with conventional beamforming using focused transmit beams. In the present study, the minimum variance beamformer was examined for improvement of the spatial resolution in high-frame-rate ultrasound. In conventional minimum variance beamforming, the spatial covariance matrix of ultrasonic echo signals received by individual transducer elements is obtained without considering the directivity of the transducer element. By omitting the element directivity, the error in estimation of the desired signal (i.e., the echo from the focal point) increases, and as a result, the improvement of the spatial resolution is degraded. In the present study, the element directivity was taken into account in estimation of the spatial covariance matrix used in minimum variance beamforming. The effect of the element directivity on adaptive beamforming was evaluated by computer simulation and basic experiments using a phantom. In parallel beamforming with the conventional DAS beamformer, the lateral spatial resolution, which was evaluated from the lateral full width at half maximum of the echo amplitude profile in the basic experiment, was 0.50 mm. Using conventional amplitude and phase estimation (APES) beamforming, the lateral spatial resolution was improved to 0.37 mm. The lateral spatial resolution was further improved to 0.30 mm using the modified APES beamforming by considering the element directivity. Image contrast and contrast-to-noise ratios, respectively, were -12.3 and 6.5 dB (DAS), -32.8 and -11.3 dB (APES), and -7.0 and 3.1 dB (modified APES).

GPU-based minimum variance beamformer for synthetic aperture imaging of the eye

Minimum variance (MV) beamforming has emerged as an adaptive apodization approach to bolster the quality of images generated from synthetic aperture ultrasound imaging methods that are based on unfocused transmission principles. In this article, we describe a new high-speed, pixel-based MV beamforming framework for synthetic aperture imaging to form entire frames of adaptively apodized images at real-time throughputs and document its performance in swine eye imaging case examples. Our framework is based on parallel computing principles, and its real-time operational feasibility was realized on a six-GPU (graphics processing unit) platform with 3,072 computing cores. This framework was used to form images with synthetic aperture imaging data acquired from swine eyes (based on virtual point-source emissions). Results indicate that MV-apodized image formation with video-range processing throughput (>20 fps) can be realized for practical aperture sizes (128 channels) and frames with λ/2 pixel spacing. Also, in a corneal wound detection experiment, MV-apodized images generated using our framework revealed apparent contrast enhancement of the wound site (10.8 dB with respect to synthetic aperture images formed with fixed apodization). These findings indicate that GPU-based MV beamforming can, in real time, potentially enhance image quality when performing synthetic aperture imaging that uses unfocused firings.

Capon beamforming and moving objects--an analysis of lateral shift-invariance

If an ultrasound imaging system provides a presentation of a moving object which is sensitive to small spatial shifts, the system is said to be locally spatially shift-variant. This can happen, for instance, if the axial or lateral sampling is insufficient. The Capon beamformer has been shown to provide increased lateral resolution in ultrasound images. Increased lateral resolution should demand denser lateral sampling. However, in previous literature on Capon beamforming for medical ultrasound imaging, only single-frame scenarios have been simulated. Temporal behavior and effects caused by the increased resolution and lack of oversampling have therefore been neglected. In this paper, we analyze the local lateral shift-invariance of the Capon beamformer when imaging moving objects. We show that insufficient lateral sampling makes an imaging system based on the Capon beamformer laterally shift-variant. Different methods for oversampling on transmit and receive are then discussed and investigated to improve on the Capon beamformer. It is shown that lateral shift-invariance can be improved by oversampling based on phase rotation on receive without affecting the acquisition frame rate and with a minor change in processing complexity.