Eigenspace based minimum variance beamforming applied to ultrasound imaging of acoustically hard tissues

Timing-synchronized passive ultrasound imaging of cavitation using eigenspace-based minimum variance beamforming and principal component analysis

BACKGROUND

Passive ultrasound imaging (PUI) allows to spatially resolve cavitation triggered during ultrasound irradiation, its application in therapeutic ultrasound has been gaining attention in recent years. The diffraction mode of the imaging transducer greatly limits the PUI axial resolution, which can be improved by transmit-receive synchronization and employment of delay sum beamforming (DSB) when transmitting short pulses, however, DSB yields poor performance in resolution and anti-interference.

PURPOSE

Inspired by adaptive beamforming and its low-complexity algorithm in active imaging field, this paper aims to develop an improved timing-synchronized PUI (TSPUI) algorithm for detection of short-pulse transmission-induced cavitation.

METHODS

The passive array data collected by timing synchronization is processed by minimum variance beamforming (MVB), whose weights are optimized by projection on the eigendecomposed signal subspace, that is, eigenspace-based MVB (EMVB), with the sum of the flight times on the transmitting and receiving paths as the delay. Applying principal component analysis (PCA) on the pre-collected MVB weight samples, a conversion matrix is constructed to allow the matrix inversion and eigendecomposition involved in weight calculation to be performed in a low dimension. The algorithm performance is confirmed by experiments, where a high-intensity focused ultrasound transducer and a linear-array transducer configured in a common parallel or vertical manner are employed for cavitation induction and cavitation imaging, and evaluated with the established indicators.

RESULTS

Reducing the eigenvalue threshold coefficient allows more sidelobes to be removed, and choosing an appropriate principal component number can reduce the time cost while guaranteeing the reconstruction quality. EMVB-PCA provides high resolution and anti-interference performance relative to DSB, with a reduction of over 60% in the point spread area and over 14 dB in the sidelobe and noise level, meanwhile, its time cost is considerably lower than EMVB, with a reduction of over 80%. Additionally, constructing the conversion matrix by simulation is feasible and valid, providing convenience for real imaging.

CONCLUSIONS

EMVB-PCA allows for high-quality TSPUI reconstruction of cavitation at a fast rate, providing an effective tool for detecting short-duration cavitation and further benefiting short-pulse therapeutic ultrasound applications.

Image-Derived Skeletal Muscle Activation Metric Map: A Forearm Study Using Ultra-Fast Ultrasound Imaging and High-Density Electromyography

OBJECTIVE

Quantification of the skeletal muscle response can help better understand the fundamentals of the musculoskeletal system and can serve as a diagnostic measure or recovery assessment tool during rehabilitation for neurological injuries. Surface electromyography (EMG) is commonly used to measure muscle activity, but it is limited to detecting myoelectric signals without anatomy associated information. In this study, we proposed to use ultra-fast ultrasound imaging and introduced a new image analysis methodology to quantify a muscle's spatial-temporal mechanical response.

METHODS

The methodology is based on analyzing the spatial-temporal change of the impulsive kinetic energy during the period of muscle contraction. The analysis can derive an anatomy-registered muscle activation metric map that localizes regions of muscle activation. To demonstrate this, we intentionally evoked regional muscle responses in five participants without disabilities by electrically stimulating the median nerve and individual forearm muscle groups, respectively. Both ultrasound images and high-density EMG (HD-EMG) data were recorded and processed.

RESULTS

We presented the ultrasound image-derived activation localization from five participants and compared the results with HD-EMG measurements.

CONCLUSION

The comparison indicates a good resemblance for describing muscle recruitment pattern.

SIGNIFICANCE

The proposed methodology can potentially become an alternative or complementary approach to surface EMG for the study of skeletal muscle activation and for diagnosis and prognosis in clinical settings.

A Heterogeneous Ultrasound Open Scanner for the Real-Time Implementation of Computationally Demanding Imaging Methods

Ultrasound (US) open scanners have recently boosted the development and validation of novel imaging techniques. They are usually split into hardware- or software-oriented systems, depending on whether they process the echo data using embedded field programmable gate arrays (FPGAs)/digital signal processors (DSPs) or a graphics processing unit (GPU) on a host personal computer (PC). The goal of this work was to realize a high-performance heterogeneous open scanner capable of leveraging the strengths of both hardware- and software-oriented systems. The elaboration power of the 256-channel ultrasound advanced open platform (ULA-OP 256) was further enhanced by embedding a compact co-processing (CP) GPU system-on-module (SoM). By carefully avoiding latencies and overheads through low-level optimization work, an efficient peripheral component interconnect express (PCIe) communication interface was established between the GPU and the processing devices onboard the ULA-OP 256. As a proof of concept of the enhanced system, the high frame rate (HFR) color flow mapping (CFM) technique was implemented on the GPU SoM and tested. Compared to a previous DSP-based implementation, higher real-time frame rates were achieved together with unprecedented flexibility in setting crucial parameters such as the ensemble length (EL). For example, by setting EL =64 and a continuous-time high-pass filter (HPF), the flow was investigated with high temporal and spatial resolution in the femoral vein bifurcation (frame rate =1.1 kHz) and carotid artery bulb (4.3 kHz), highlighting the flow disturbances due to valve aperture and secondary velocity components, respectively. The results of this work promote the development of other computational-expensive processing algorithms in real time and may inspire the next generation of the US high-performance heterogeneous scanners.

Clairvoyant performance bounds for adaptive beamforming in pulse-echo imaging

In adaptive beamforming, the array signal processing adjusts its sensor delays and weights based on the incoming data. In conventional beamforming, these parameters are instead given from a predefined model. Adaptive beamformers can improve measurement precision by dynamically rejecting spatial interference. While an established theory is available on the behavior of adaptive beamformers in textbook scenarios, their expected performance on realistic pulse-echo imaging scenes is still mostly uncharted. Imaging performance can be evaluated by individual pixel precision and aggregated metrics such as resolution and contrast. The achievable gain is strongly related to the sparsity of the scene and the availability of data to appropriately estimate the spatial covariance matrix. In pulse-echo measurements, the nonstationary interference poses a special problem for adaptive beamforming, which is a current research question of academic and industrial interest. The current work establishes a performance bound for adaptive beamforming in simulated realistic pulse-echo scenarios. This is derived and numerically implemented as the clairvoyant minimum variance distortionless response beamformer. The proposed framework allows for an a priori assessment of the applicability of adaptive beamforming, for a given scenario. The performance of the implemented algorithms can be directly compared with the theoretical limit in a simulated environment.

Vessel recovery using ultrasound localisation microscopy: An in silico comparative study between minimum variance and delay-and-sum beamformers

The use of particle localisation and tracking algorithms on Contrast Enhanced Ultrasound (CEUS) or other ultrasound mode image data containing sparse microbubble (MB) populations, can produce super-resolved vascularization maps. Typically such data stem from conventional delay and sum (DAS) beamforming that is used widely in ultrasound imaging modes. Recently, adaptive beamforming has shown significant improvement in spatial resolution, but its value to super-resolution image analysis approaches is not fully understood. The in silico study here evaluates the performance of combining minimum variance beamformers (MV BF), established to provide improved lateral resolution, compared to DAS BFs with single particle detection. The isolated effect of a range of simplified image-affecting factors such as flow profile, pulse length, noise, vessel separations and data availability is considered. The study aims to assess the vessel recovery performance using the different beamformers and investigate the link with MB detection and localisation. The MV BF was shown to provide improved microvessel position accuracy compared to conventional DAS BFs. In particular, vessel separations between 0.3-4 λ provided superior localisation uncertainty with the MV. In addition, for a separation of 0.36λ, vessel recovery was achieved with both methods but the use of MV eliminated artifacts that appear as additional vessels. These results were found to be linked to improved MB detection and localisation for the MV BF, which is proposed as suitable for testing in Ultrasound Localisation Microscopy (ULM) imaging using patient data.

Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence

For ultrasound multi-angle plane wave (PW) imaging, the coherent PW compounding (CPWC) method provides limited image quality because of its conventional delay-and-sum beamforming. The delay-multiply-and-sum (DMAS) method is a coherence-based algorithm that improves image quality by introducing signal coherence among either receiving channels or PW transmit angles into the image output. The degree of signal coherence in DMAS is conventionally a global value for the entire image and thus the image resolution and contrast in the target region improves at the cost of speckle quality in the background region. In this study, the adaptive DMAS (ADMAS) is proposed such that the degree of signal coherence relies on the local characteristics of the image region to maintain the background speckle quality and the corresponding contrast-to-noise ratio (CNR). Subsequently, the ADMAS algorithm is further combined with minimum variance (MV) beamforming to increase the image resolution. The optimal MV estimation is determined to be in the direction of the PW transmit angle (Tx) for multi-angle PW imaging. Our results show that, using the PICMUS dataset, TxMV-ADMAS beamforming significantly improves the image quality compared with CPWC. When the p value is globally fixed to 2 as in conventional DMAS, though the main-lobe width and the image contrast in the experiments improve from 0.57 mm and 27.0 dB in CPWC, respectively, to 0.24 mm and 38.0 dB, the corresponding CNR decreases from 12.8 to 11.3 due to the degraded speckle quality. With the proposed ADMAS algorithm, however, the adaptive p value in DMAS beamforming helps to restore the CNR value to the same level of CPWC while the improvement in image resolution and contrast remains evident.

On the physics of ultrasound transmission for in-plane needle tracking in guided interventions

Objective.In ultrasound (US) guided interventions, the accurate visualization and tracking of needles is a critical challenge, particularly during in-plane insertions. An inaccurate identification and localization of needles lead to severe inadvertent complications and increased procedure times. This is due to the inherent specular reflections from the needle with directivity depending on the angle of incidence of the US beam, and the needle inclination.Approach.Though several methods have been proposed for improved needle visualization, a detailed study emphasizing the physics of specular reflections resulting from the interaction of transmitted US beam with the needle remains to be explored. In this work, we discuss the properties of specular reflections from planar and spherical wave US transmissions respectively through multi-angle plane wave (PW) and synthetic transmit aperture (STA) techniques for in-plane needle insertion angles between 15°-50°.Main Results.The qualitative and quantitative results from simulations and experiments reveal that the spherical waves enable better visualization and characterization of needles than planar wavefronts. The needle visibility in PW transmissions is severely degraded by the receive aperture weighting during image reconstruction than STA due to greater deviation in reflection directivity. It is also observed that the spherical wave characteristics starts to alter to planar characteristics due to wave divergence at large needle insertion depths.Significance.The study highlights that synergistic transmit-receive imaging schemes addressing the physical properties of reflections from the transmit wavefronts are imperative for the precise imaging of needle interfaces and hence have strong potential in elevating the quality of outcomes from US guided interventional practices.

Combining ADMIRE and MV to Improve Image Quality

Aperture domain model image reconstruction (ADMIRE) is a frequency-domain, model-based beamformer, in part designed for removing reverberation and off-axis clutter. Minimum variance (MV) is alternatively designed to reduce off-axis interference and improve lateral resolution. MV is known to be less effective in high incoherent noise scenarios, and its performance in the presence of reverberation has not been evaluated. By implementing ADMIRE before MV, the benefits of both these beamformers can be achieved. In this article, the assumptions of MV are discussed, specifically their relationship to reverberation clutter. The use of ADMIRE as a preprocessing step to suppress noise from simulations with linear scanning and in vivo curvilinear kidney data is demonstrated, and both narrowband and broadband implementations of MV are applied. With optimal parameters, ADMIRE + MV demonstrated sizing improvements over MV alone by an average of 52.1% in 0-dB signal-to-clutter ratio reverberation cyst simulations and 14.5% in vivo while improving the contrast ratio compared to ADMIRE alone by an average of 15.1% in simulations and 14.0% in vivo. ADMIRE + MV demonstrated a consistent improvement compared to DAS, MV, and ADMIRE both in terms of sizing and contrast ratio.

Investigation on improving performance of adaptive beamformer by statistical analysis of ultrasonic echoes

Minimum variance (MV) beamformers have been introduced in medical ultrasound imaging to improve image quality. In most cases, the MV beamformers have been investigated in terms of resolution improvement. However, the contrast-to-noise ratio (CNR) is also a clinically important metrics and gathers attention recently. In this study, we examined the diagonal loading parameter σ in MV beamforming and determined its appropriate value by evaluating image quality evaluation metrics including CNR. In order to further improve the image quality, a method for determining the value of σ based on the difference in statistical properties of received ultrasonic echo signals was also investigated. The phantom experimental results showed that the proposed method achieved a better CNR than the conventional MV beamformer while keeping resolution significantly better than that in delay-and-sum beamforming.

A Low-Complexity and High-Resolution Beamformer for Portable Medical Ultrasound Imaging

So far, researchers have proposed various methods to improve the quality of medical ultrasound imaging. However, in portable medical ultrasound imaging systems, features, such as low cost and low power consumption for battery longevity, are very important. Hence, most of the proposed algorithms have not been proper substitutes for the delay and sum (DAS) algorithm in portable clinical applications due to their high computational complexity and cost. In this article, a new algorithm is presented concentrating on reducing the computational complexity based on a technique that separates the signal from the correlated interferences to overcome the negative characteristics, particularly for portable applications such as high price, high power consumption, and off-axis clutters in the azimuth direction. Also, the proposed algorithm yields a higher contrast compared to that of the DAS algorithm while achieving a similar computation complexity order of O ( n ) similar to the DAS algorithm. Furthermore, the performed simulations confirm that the proposed method is able to achieve a better resolution almost twice as that of the filtered delay multiply and sum (F-DMAS) algorithm with the same sidelobe level.

Achieving depth-independent lateral resolution in AR-PAM using the synthetic-aperture focusing technique

Acoustic-resolution photoacoustic microscopy (AR-PAM) is a promising imaging modality that renders images with ultrasound resolution and extends the imaging depth beyond the optical ballistic regime. To achieve a high lateral resolution, a large numerical aperture (NA) of a focused transducer is usually applied for AR-PAM. However, AR-PAM fails to hold its performance in the out-of-focus region. The lateral resolution and signal-to-noise ratio (SNR) degrade substantially, thereby leading to a significantly deteriorated image quality outside the focal area. Based on the concept of the synthetic-aperture focusing technique (SAFT), various strategies have been developed to address this challenge. These include 1D-SAFT, 2D-SAFT, adaptive-SAFT, spatial impulse response (SIR)-based schemes, and delay-multiply-and-sum (DMAS) strategies. These techniques have shown progress in achieving depth-independent lateral resolution, while several challenges remain. This review aims to introduce these developments in SAFT-based approaches, highlight their fundamental mechanisms, underline the advantages and limitations of each approach, and discuss the outlook of the remaining challenges for future advances.

Applying Coherence Factor to Double-Stage Delay Multiply and Sum Beamforming in Medical Ultrasound Imaging

The Filtered Delay Multiply and Sum (F-DMAS) beamforming algorithm has recently been proposed to improve the resolution and contrast in ultrasound imaging. Based on F-DMAS, some researchers have introduced an alternative named Double-Stage Delay Multiply and Sum (DS-DMAS), which can be considered as an enhanced version of F-DMAS. The DS-DMAS expands the DMAS algorithm to synthesize some new signals, which are then beamformed using a DMAS beamformer. However, the way to generate new signals in DS-DMAS can be thought of as a Delay and Sum (DAS) operation. There are some shortages in the DAS algorithm, so we proposed a new approach named Coherence Factor based Double-Stage Delay Multiply and Sum (DSDMAS-CF) to address these issues. The key idea of our method is to optimize the DAS operation in DSDMAS. Therefore, a modified coherence factor (CF) is applied to weight each item in DS-DMAS. The simulation, experimental and in vivo data are used to compare the performance between DAS, F-DMAS, DS-DMAS and DS-DMAS-CF. The results show that the DS-DMAS-CF gets better resolution and contrast in comparison with the other three algorithms.

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.

Instantaneous Frequency Image

The instantaneous frequency (IF) image is proposed in this work. It is obtained by the differentiation of the instantaneous phase (IP) image, which in turn is calculated by replacing the amplitude information with the IP in the delay-and-sum beamforming. The IP image is a coherence factor that reduces artifacts and sidelobes influence, and it will be shown that the IF image will keep these same positive characteristics. In amplitude images the reflector representation level varies according to the experimental conditions, even using time-gain compensation. In IP images, the reflector is represented by a - π to π rad variation. An important feature of the IF image is that a reflector is represented by a constant level that is determined by the central frequency of the signal. Farther reflectors are represented with similar magnitudes as closer ones, being less influenced by distance than IP images and resulting in better contrast. Amplitude, IP, and IF images are obtained from point spread function simulations and a medical phantom in different experimental cases: vertical distances, contrast reflectors, axial and lateral separation, and a sparse array. The improper choice of dynamic range can result in low contrast or nondetection of a reflector. For the IF image, the dynamic range is determined by the central frequency of the signal and the zero-mean Gaussian distribution of the IF of noise. The IF image can be used to improve reflector detection, as additional information to assist the interpretation of pixels intensities in conventional amplitude images, or as a new coherence factor.

Image Quality Enhancement Using a Deep Neural Network for Plane Wave Medical Ultrasound Imaging

Plane wave imaging (PWI), a typical ultrafast medical ultrasound imaging mode, adopts single plane wave emission without focusing to achieve a high frame rate. However, the imaging quality is severely degraded in comparison with the commonly used focused line scan mode. Conventional adaptive beamformers can improve imaging quality at the cost of additional computation. In this article, we propose to use a deep neural network (DNN) to enhance the performance of PWI while maintaining a high frame rate. In particular, the PWI response from a single point target is used as the network input, while the focused scan response from the same point serves as the desired output, which is the main contribution of this method. To evaluate the performance of the proposed method, simulations, phantom experiments and in vivo studies are conducted. The delay-and-sum (DAS), the coherence factor (CF), a previously proposed deep learning-based method and the DAS with focused scan are used for comparison. Numerical metrics, including the contrast ratio (CR), the contrast-to-noise ratio (CNR), and the speckle signal-to-noise ratio (sSNR), are used to quantify the performance. The results indicate that the proposed method can achieve superior resolution and contrast performance. Specifically, the proposed method performs better than the DAS in all metrics. Although the CF provides a higher CR, its CNR and sSNR are much lower than those of the proposed method. The overall performance is also better than that of the previous deep learning method and at the same level with focused scan performance. Additionally, in comparison with the DAS, the proposed method requires little additional computation, which ensures high temporal resolution. These results validate that the proposed method can achieve a high imaging quality while maintaining the high frame rate associated with PWI.

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.

The Generalized Contrast-to-Noise Ratio: A Formal Definition for Lesion Detectability

In the last 30 years, the contrast-to-noise ratio (CNR) has been used to estimate the contrast and lesion detectability in ultrasound images. Recent studies have shown that the CNR cannot be used with modern beamformers, as dynamic range alterations can produce arbitrarily high CNR values with no real effect on the probability of lesion detection. We generalize the definition of CNR based on the overlap area between two probability density functions. This generalized CNR (gCNR) is robust against dynamic range alterations; it can be applied to all kind of images, units, or scales; it provides a quantitative measure for contrast; and it has a simple statistical interpretation, i.e., the success rate that can be expected from an ideal observer at the task of separating pixels. We test gCNR on several state-of-the-art imaging algorithms and, in addition, on a trivial compression of the dynamic range. We observe that CNR varies greatly between the state-of-the-art methods, with improvements larger than 100%. We observe that trivial compression leads to a CNR improvement of over 200%. The proposed index, however, yields the same value for compressed and uncompressed images. The tested methods showed mismatched performance in terms of lesion detectability, with variations in gCNR ranging from -0.08 to +0.29. This new metric fixes a methodological flaw in the way we study contrast and allows us to assess the relevance of new imaging algorithms.

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.

Region-of-Interest-Based Closed-Loop Beamforming for Spinal Ultrasound Imaging

Clear visualization of spine structures in ultrasound imaging is difficult due to factors such as specular reflection, off-axis energy, and reverberation artifacts. The received channel data from the spine are often tilted even after delay correction, resulting in signal cancellation during the beamforming process. Conventional beamformers are not designed to tackle this issue. This paper proposes a closed-loop beamforming method which feeds back the location of the spine to the beamforming process so that backscattered bone signals can be aligned prior to the beamforming. To suppress the weak soft tissue and reverberation artifacts and increase the contrast of bones, a tensor-based filtering is employed prior to the cross-correlation-based alignment. Directional filtering is also employed to improve the bone surface detection. Phantom studies show improvement on the sharpness of the spine without shape distortion. In vivo results confirm significant contrast improvement of spinal structures. Compared with the conventional delay-and-sum beamforming, the proposed method improves the contrast ratio (CR) of the spine from 0.56 to 0.96. The 6-dB width of bone surfaces is also reduced by 51%.

Sparsity-based beamforming to enhance two-dimensional linear-array photoacoustic tomography

In linear-array photoacoustic imaging (PAI), beamforming methods can be used to reconstruct the images. Delay-and-sum (DAS) beamformer is extensively used due to its simple implementation. However, this algorithm results in high level of sidelobes and low resolution. In this paper, it is proposed to form the photoacoustic (PA) images through a regularized inverse problem to address these limitations and improve the image quality. We define a forward/backward problem of the beamforming and solve the inverse problem using a sparse constraint added to the model which forces the sparsity of the output beamformed data. It is shown that the proposed Sparse beamforming (SB) method is robust against noise due to the sparsity nature of the problem. Numerical results show that the SB method improves the signal-to-noise ratio (SNR) for about 98.69 dB, 82.26 dB and 74.73 dB, in average, compared to DAS, delay-multiply-and-sum (DMAS) and double stage-DMAS (DS-DMAS), respectively. Also, quantitative evaluation of the experimental results shows a significant noise reduction using SB algorithm. In particular, the contrast ratio of the wire phantom at the depth of 30 mm is improved about 103.97 dB, 82.16 dB and 65.77 dB compared to DAS, DMAS and DS-DMAS algorithms, respectively, indicating a better performance of the proposed SB in terms of noise reduction.

The Effect of Dynamic Range Alterations in the Estimation of Contrast

Many adaptive beamformers claim to produce images with increased contrast, a feature that could enable a better detection of lesions and anatomical structures. Contrast is often quantified using the contrast ratio (CR) and the contrast-to-noise ratio (CNR). The estimation of CR and CNR can be affected by dynamic range alterations (DRAs), such as those produced by a trivial gray-level transformation. Thus, we can form the hypothesis that contrast improvements from adaptive beamformers can, partly, be due to DRA. In this paper, we confirm this hypothesis. We show evidence on the influence of DRA on the estimation of CR and CNR and on the fact that several methods in the state of the art do alter the DR. To study this phenomenon, we propose a DR test (DRT) to estimate the degree of DRA and we apply it to seven beamforming methods. We show that CR improvements correlate with DRT with [Formula: see text] in simulated data and [Formula: see text] in experiments. We also show that DRA may lead to increased CNR values, under some circumstances. These results suggest that claims on lesion detectability, based on CR and CNR values, should be revised.

Image improvement in linear-array photoacoustic imaging using high resolution coherence factor weighting technique

Background

In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF.

Results

The higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively.

Conclusion

Proposed method provides a high resolution along with a low level of sidelobes for PAI.

Plane wave imaging combined with eigenspace-based minimum variance beamforming using a ring array in ultrasound computed tomography

BACKGROUND

Ultrasound computed tomography (USCT) is usually realized with a ring array. It can provide better imaging performance and more tissue information by emitting and receiving the ultrasound signal in different directions simultaneously. However, USCT imaging is usually applied with the synthetic aperture (SA) emission method, which leads to a long scanning time with a large number of elements on the ring array. The echo image can provide the structural information, and has a higher resolution than maps of other parameters in USCT. Hence, we proposed plane wave (PW) imaging for ring array to acquire the echo wave and reduce the scanning time considerably.

RESULTS

In this paper, an emitting and receiving process was proposed to realize plane wave imaging with a ring array. With the proposed scanning method, the number of emission events can be reduced greatly. A beamforming method based on the eigenspace-based minimum variance (ESBMV) was also combined with the scanning method. With ESBMV beamformer, the resolution and contrast ratio of reconstruction result can be maintained or even improved under a fewer-emissions condition. We validated the method using both computer simulations with Field II and phantom experiments with a ring array of 512 elements. The Verasonics^® system was used to transmit and receive the ultrasound signal in the phantom experiments.

CONCLUSIONS

According to the results of the experiments, the imaging results will have a better contrast ratio with a higher emitting energy. Additionally, the scanning time with the proposed method can be only one-tenth of that with the SA emission method, while the echo imaging performance still remains at a similar level or even better.

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.

Joint Subarray Coherence and Minimum Variance Beamformer for Multitransmission Ultrasound Imaging Modalities

Multitransmission modalities, such as plane wave compounding and synthetic aperture imaging, are promising techniques for ultrafast ultrasound imaging. Adaptive beamformers have been proposed to improve the imaging quality. Two common categories of adaptive beamformers are the minimum variance (MV)-based beamformers and the coherence factor (CF)-based beamformers. The MV can significantly improve the resolution while lacking robustness. It is also computationally expensive for multitransmission modalities. The CF can increase the contrast while over-suppressing some desired signals. In this paper, we propose a novel beamformer for better imaging quality in multitransmission ultrasound modalities. Specifically, the MV weighting process is applied to the receiving and transmitting beamforming. The spatial smoothing technique is modified for both dimensions to enhance the robustness. Then, the CF-based weights are calculated using the MV beamformed output. The submatrix technique is also used in the CF process to avoid over-suppression. Simulations and experiments are conducted to evaluate the performance of the proposed method. The results show that it can preserve the high resolution of MV and the high contrast of CF. Compared with the traditional compounding method, the full-width at half-maximum is smaller and the contrast ratio is significantly increased. Anatomic structures of an in vivo human carotid artery are more distinguishable. Because of the spatial smoothing in both dimensions, the proposed beamformer also has high robustness against the channel noise and sound velocity errors.

Eigenspace generalized sidelobe canceller combined with SNR dependent coherence factor for plane wave imaging

Background

The eigenspace generalized sidelobe canceller (EGSC) beamformer combined with a signal-to-noise ratio (SNR) dependent coherence factor (CF) is suggested for coherent plane wave compounding (PW) imaging. Conventional CF based methods such as generalized CF and subarray CF can improve the image quality, however, they are not suitable for low SNR. On the other hand, the EGSC CF based approach can introduce improvements in image quality, however, in PW imaging is susceptible to suffer from degradation due to low SNR which leads to a poor image quality. To overcome this limitation, the SNR dependent CF method is suggested for application in such situations due to its ability to control the SNR levels.

Methods

The Field II and the Verasonics ultrasound imaging system with a L11-4v array transducer with a contrast resolution phantom were used to capture the plane wave sequences of simulation and experimental data, respectively. The performance evaluation using full width at half maximum (FWHM), contrast (CR and CNR) and the speckle statistics by using the signal to noise ratio (SNR) complemented by the Rayleigh distribution analysis was performed. In order to evaluate the performance of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_{3}$$\end{document}EGSC3 (the SNR CF) beamformer, the comparison is done with particular importance to other CF-based approaches such as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_{1}$$\end{document}EGSC1 (the generalized CF) and, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_{2}$$\end{document}EGSC2 (the subarray CF) respectively.

Results

Taking DAS as reference, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_3$$\end{document}EGSC3 showed 30.3 and 39.5% of improvement for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {CR(dB)}$$\end{document}CR(dB) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {CNR}$$\end{document}CNR, respectively, when using experimental data. The proposed method also slightly outperforms the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_1$$\end{document}EGSC1 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_2$$\end{document}EGSC2 methods for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {CR(dB)}$$\end{document}CR(dB), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {CNR}$$\end{document}CNR, and speckle statistics assessment.

Conclusion

The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {EGSC}_3$$\end{document}EGSC3 is, therefore, suitable for CPWC by improving the spatial resolution and contrast while preserving the speckle pattern.

Efficient nonlinear beamformer based on P'th root of detected signals for linear-array photoacoustic tomography: application to sentinel lymph node imaging

In linear-array transducer-based photoacoustic (PA) imaging, B-scan PA images are formed using the raw channel PA signals. Delay-and-sum (DAS) is the most prevalent algorithm due to its simple implementation, but it leads to low-quality images. Delay-multiply-and-sum (DMAS) provides a higher image quality in comparison with DAS while it imposes a computational burden of O  (  M2  )  . We introduce a nonlinear (NL) beamformer for linear-array PA imaging, which uses the p'th root of the detected signals and imposes the complexity of DAS [O  (  M  )  ]. The proposed algorithm is evaluated numerically and experimentally [wire-target and in-vivo sentinel lymph node (SLN) imaging], and the effects of the parameter p are investigated. The results show that the NL algorithm, using a root of p (NL_p), leads to lower sidelobes and higher signal-to-noise ratio compared with DAS and DMAS, for (p  >  2). The sidelobes level (for the wire-target phantom), at the depth of 11.4 mm, are about -31, -52, -52, -67, -88, and -109  dB, for DAS, DMAS, NL_2, NL_3, NL_4, and NL_5, respectively, indicating the superiority of the NL_p algorithm. In addition, the best value of p for SLN imaging is reported to be 12.

Photoacoustic image formation based on sparse regularization of minimum variance beamformer

Delay-and-sum (DAS) is the most common algorithm used in photoacoustic (PA) image formation. However, this algorithm results in a reconstructed image with a wide mainlobe and high level of sidelobes. Minimum variance (MV), as an adaptive beamformer, overcomes these limitations and improves the image resolution and contrast. In this paper, a novel algorithm, named Modified-Sparse-MV (MS-MV), is proposed in which a ℓ 1-norm constraint is added to the MV minimization problem after some modifications, in order to suppress the sidelobes more efficiently, compared to MV. The added constraint can be interpreted as the sparsity of the output of the MV beamformed signals. Since the final minimization problem is convex, it can be solved efficiently using a simple iterative algorithm. The numerical results show that the proposed method, MS-MV beamformer, improves the signal-to-noise (SNR) about 19.48 dB, in average, compared to MV. Also, the experimental results, using a wire-target phantom, show that MS-MV leads to SNR improvement of about 2.64 dB in comparison with the MV.

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.

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.

Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

Accumulated Angle Factor-Based Beamforming to Improve the Visualization of Spinal Structures in Ultrasound Images

In recent years, ultrasound has been increasingly used to guide needle insertion procedures for spinal anesthesia. The primary anatomical targets are facet joints and epidural spaces. For these procedures, accurate visualization of the spine anatomy is of critical importance. Challenges arising from the interactions between the ultrasound beam and spinal structures including tilt caused by specular reflections, off-axis interference, and reverberations often result in weakened and blurred vertebra surfaces. Previously, adaptive beamforming methods have been proposed to improve the resolution and contrast. However, most of these methods are not specialized for improving the contrast of specular targets like bones. In this paper, we propose an accumulated angle factor (AAF)-based beamforming method customized for bone surface enhancement. This approach applies a Hilbert transform on delay compensated channel data across the receive aperture. The accumulated phase change across the receive aperture is then calculated and utilized as the weight in the beamforming output. We compared our method with classical delay and sum (DAS) beamforming method and adaptive beamforming methods such as Wiener, phase coherence factor (PCF), CF, and generalized CF (GCF) beamforming. In 12 volunteer data sets, the mean contrast ratio between the vertebrae surface and the surrounding tissue for DAS, Wiener, PCF, CF, GCF, and the proposed AAF methods are 0.49, 0.64, 0.82, 0.77, 0.76, and 0.91, respectively. The contrast is significantly improved in the proposed method.

Ultrafast Ultrasound Imaging Using Combined Transmissions With Cross-Coherence-Based Reconstruction

Plane-wave-based ultrafast imaging has become the prevalent technique for non-conventional ultrasound imaging. The image quality, especially in terms of the suppression of artifacts, is generally compromised by reducing the number of transmissions for a higher frame rate. We hereby propose a new ultrafast imaging framework that reduces not only the side lobe artifacts but also the axial lobe artifacts using combined transmissions with a new coherence-based factor. The results from simulations, in vitro wire phantoms, the ex vivo porcine artery, and the in vivo porcine heart show that our proposed methodology greatly reduced the axial lobe artifact by 25±5 dB compared with coherent plane-wave compounding (CPWC), which was considered as the ultrafast imaging standard, and suppressed side lobe artifacts by 15 ± 5 dB compared with CPWC and coherent spherical-wave compounding. The reduction of artifacts in our proposed ultrafast imaging framework led to a better boundary delineation of soft tissues than CPWC.

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.

Effects of Phase Aberration and Phase Aberration Correction on the Minimum Variance Beamformer

The minimum variance (MV) beamformer has the potential to enhance the resolution and contrast of ultrasound images but is sensitive to steering vector errors. Robust MV beamformers have been proposed but mainly evaluated in the presence of gross sound speed mismatches, and the impact of phase aberration correction (PAC) methods in mitigating the effects of phase aberration in MV beamformed images has not been explored. In this study, an analysis of the effects of aberration on conventional MV and eigenspace MV (ESMV) beamformers is carried out. In addition, the impact of three PAC algorithms on the performance of MV beamforming is analyzed. The different beamformers were tested on simulated data and on experimental data corrupted with electronic and tissue-based aberration. It is shown that all gains in performance of the MV beamformer with respect to delay-and-sum (DAS) are lost at high aberration strengths. For instance, with an electronic aberration of 60 ns, the lateral resolution of DAS degrades by 17% while MV degrades by 73% with respect to the images with no aberration. Moreover, although ESMV shows robustness at low aberration levels, its degradation at higher aberrations is approximately the same as that of regular MV. It is also shown that basic PAC methods improve the aberrated MV beamformer. For example, in the case of electronic aberration, multi-lag reduces degradation in lateral resolution from 73% to 28% and contrast loss from 85% to 25%. These enhancements allow the combination of MV and PAC to outperform DAS and PAC and ESMV in moderate and strong aberrations. We conclude that the effect of aberration on the MV beamformer is stronger than previously reported in the literature and that PAC is needed to improve its clinical potential.

Specular Beamforming

Acoustically hard objects, such as bones, needles, or catheters, are poorly visualized in conventional ultrasound images. These objects behave like acoustic mirrors and reflect sound in specific directions. Soft tissue and diffusive reflectors scatter sound in a broad range of directions. Conventional delay-and-sum beamforming is based on the assumption of a purely scattering domain with relatively weak reflectivity. We present an adaptive beamforming technique that takes into account the physics of specular reflection. Patterns predicted by the law of reflection are detected across the pool of received data and used to enhance the visualization of specular energy. This technique can be applied to any synthetic imaging sequence. Here, it is applied to synthetic transmit aperture imaging. In vitro experiments show a clear improvement in target visibility and an increase of 30 to 60 dB in signal-to-noise ratio.

Pulse-Inversion Subharmonic Ultrafast Active Cavitation Imaging in Tissue Using Fast Eigenspace-Based Adaptive Beamforming and Cavitation Deconvolution

Pulse-inversion subharmonic (PISH) imaging can display information relating to pure cavitation bubbles while excluding that of tissue. Although plane-wave-based ultrafast active cavitation imaging (UACI) can monitor the transient activities of cavitation bubbles, its resolution and cavitation-to-tissue ratio (CTR) are barely satisfactory but can be significantly improved by introducing eigenspace-based (ESB) adaptive beamforming. PISH and UACI are a natural combination for imaging of pure cavitation activity in tissue; however, it raises two problems: 1) the ESB beamforming is hard to implement in real time due to the enormous amount of computation associated with the covariance matrix inversion and eigendecomposition and 2) the narrowband characteristic of the subharmonic filter will incur a drastic degradation in resolution. Thus, in order to jointly address these two problems, we propose a new PISH-UACI method using novel fast ESB (F-ESB) beamforming and cavitation deconvolution for nonlinear signals. This method greatly reduces the computational complexity by using F-ESB beamforming through dimensionality reduction based on principal component analysis, while maintaining the high quality of ESB beamforming. The degraded resolution is recovered using cavitation deconvolution through a modified convolution model and compressive deconvolution. Both simulations and in vitro experiments were performed to verify the effectiveness of the proposed method. Compared with the ESB-based PISH-UACI, the entire computation of our proposed approach was reduced by 99%, while the axial resolution gain and CTR were increased by 3 times and 2 dB, respectively, confirming that satisfactory performance can be obtained for monitoring pure cavitation bubbles in tissue erosion.

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.

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.

Twofold minimum variance beamforming for enhanced ultrasound imaging

PURPOSE

To calculate the optimal weights of a minimum variance (MV) beamformer, the covariance matrix of the received data should be estimated. In ultrasound imaging, it is done through spatial smoothing. However, this technique reduces the effective aperture and consequently limits the attainable resolution. To mitigate this effect, we propose a new configuration for applying an adaptive beamforming method.

METHODS

The method is based on applying MV in a twofold configuration such that the outputs of the subarrays are combined through an adaptive MV-like beamformer, instead of simply summing them. In this way, a fully adaptive beamformer is obtained.

RESULTS

Applying the method on a phantom containing point targets has shown that off-axis signals are attenuated more in comparison to MV. This results in a lowered mainlobe width and decreased sidelobe levels. Moreover, simulation results of a cyst phantom confirm the superiority of the method over the MV in terms of contrast.

CONCLUSION

The method yields significant improvement in the resolving capability and the contrast compared with the conventional MV. At the presence of the steering vector errors, these superiorities were achieved at a cost of slightly more errors in estimating the reflectivity coefficients.

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.

Eigenspace-based beamformer using oblique signal subspace projection for ultrasound plane-wave imaging

BACKGROUND

The Eigenspace-based beamformers, by orthogonal projection of signal subspace, can remove a large part of the noise, and provide better imaging contrast upon the minimum variance beamformer. However, wrong estimate of signal and noise component may bring dark-spot artifacts and distort the signal intensity. The signal component and noise and interference components are considered uncorrelated in conventional eigenspace-based beamforming methods. In ultrasound imaging, however, signal and noise are highly correlated. Therefore, the oblique projection instead of orthogonal projection should be taken into account in the denoising procedure of eigenspace-based beamforming algorithm.

METHODS

In this paper, we propose a novel eigenspace-based beamformer based on the oblique subspace projection that allows for consideration of the signal and noise correlation. Signal-to-interference-pulse-noise ratio and an eigen-decomposing scheme are investigated to propose a new signal and noise subspaces identification. To calculate the beamformer weights, the minimum variance weight vector is projected onto the signal subspace along the noise subspace via an oblique projection matrix.

RESULTS

We have assessed the performance of proposed beamformer by using both simulated software and real data from Verasonics system. The results have exhibited the improved imaging qualities of the proposed beamformer in terms of imaging resolution, speckle preservation, imaging contrast, and dynamic range.

CONCLUSIONS

Results have shown that, in ultrasound imaging, oblique projection is more sensible and effective than orthogonal subspace projection. Better signal and speckle preservation could be obtained by oblique projection compare to orthogonal projection. Also shadowing artifacts around the hyperechoic targets have been eliminated. Implementation the new subspace identification has enhanced the imaging resolution of the minimum variance beamformer due to the increasing the signal power in direction of arrival. Also it has offered better sidelobe suppression and a higher dynamic range.

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.

Reconstruction of specular reflectors by iterative image source localization

A method is presented to reconstruct the geometry of specular reflectors with an ultrasonic array based on the image source principle. The ultrasonic beam is focused at a point in space emulating a point source within the medium. The transmitted wave interacts with the specular reflector and propagates back to the array as if it were generated by an image source. The reflected wave is analyzed with a sound source localization algorithm to estimate the image source location, and the reflector geometry is extracted using the mirror equation for spherical reflectors. The method is validated experimentally and its accuracy is studied. Under ideal conditions the method provides an accurate reconstruction of the position, orientation, and radius of curvature of specular reflectors, with errors Δr < 0.2 mm, Δα < 3°, and ΔR/R0 < 0.2, respectively. The method performs very well in the presence of high levels of thermal and speckle noise, with no degradation of the reconstruction as long as SNR(th) > -3 dB (signal-to-thermal-noise ratio) and SNR(sp) > 7 dB (signal-to-speckle-noise ratio). An iterative scheme based on the proposed method is presented to reconstruct the geometry of arbitrary reflectors by subdividing the reflector boundary into smaller segments. The iterative scheme is demonstrated both numerically and experimentally.

Resolution and brightness characteristics of short-lag spatial coherence (SLSC) images

We previously described a novel beamforming method that images the spatial correlation of an echo wave field with demonstrated applications to clutter reduction in high-noise environments. In this paper, several characteristics of the resolution and brightness of short-lag spatial coherence (SLSC) images formed by this method are compared with B-mode images formed by conventional delay-and-sum beamforming methods. Point target widths were measured to estimate resolution, the autocorrelation of image texture was measured to estimate texture size, and the contrast (i.e., brightness ratio) of clinically relevant targets was assessed. SLSC images demonstrate improved resolution and contrast with increasing values of channel noise and clutter, whereas B-mode resolution was degraded in the presence of high noise (i.e., > -12 dB channel noise-to-signal ratios) and high clutter magnitudes (i.e., > -21 dB relative to point target magnitude). Lateral resolution in SLSC images was improved with increasing lag value, whereas axial resolution was degraded with increasing correlation kernel length. The texture size of SLSC images was smaller than that of matched B-mode images. Results demonstrate that the resolution and contrast of coherence-based images depend on a range of parameters, but are generally superior to those of matched B-mode images under challenging imaging conditions.