Signal Coherence and Image Amplitude With the Filtered Delay Multiply and Sum Beamformer

A beamforming algorithm with composite multi-conditional cross correlation and range standard deviation factor for high quality ultrasound imaging

The traditional delay-and-sum (DAS) beamformer is inadequate for clutter suppression in ultrasound imaging. The coherence factor beamformer can effectively suppress clutter, but it is prone to cause dark-region artifacts during incoherent signal suppression. In this paper, the resolution and contrast of ultrasound images are improved by using a novel adaptive beamforming algorithm called composite multi-conditional cross correlation (MCC) and range standard deviation factor (CMCC-RSF). The MCC algorithm is obtained by integrating the conditional coherence and cross correlation factor, which can better balance clutter suppression ability inside the anechoic cyst and speckle background quality. Then, we propose a range standard deviation factor (RSF) to improve the resolution of MCC without destroying the speckle background. The simulation and experiment results show that compared with traditional DAS, the full-width at half-maximum of CMCC-RSF is improved by 75.14%, 47.62%, 49.27%, and 55.97%, respectively. According to the experiment results, the contrast ratio and speckle signal-to-noise ratio of CMCC-RSF are maximally improved by 154.38%, and 124.53%, respectively. In general, the proposed CMCC-RSF algorithm can improve comprehensive image quality with low relative computational complexity.

Evaluating a 3D Ultrasound Imaging Resolution of Single Transmitter/Receiver with Coding Mask by Extracting Phase Information

We are currently investigating the ultrasound imaging of a sensor that consists of a randomized encoding mask attached to a single lead zirconate titanate (PZT) oscillator for a puncture microscope application. The proposed model was conducted using a finite element method (FEM) simulator. To increase the number of measurements required by a single element system that affects its resolution, the transducer was rotated at different angles. The image was constructed by solving a linear equation of the image model resulting in a poor quality. In a previous work, the phase information was extracted from the echo signal to improve the image quality. This study proposes a strategy by integrating the weighted frequency subbands compound and a super-resolution technique to enhance the resolution in range and lateral direction. The image performance with different methods was also evaluated using the experimental data. The results indicate that better image resolution and speckle suppression were obtained by applying the proposed method.

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.

Design of Planar Differential Microphone Array Beampatterns with Controllable Mainlobe Beamwidth and Sidelobe Level

The differential microphone array, or differential beamformer, has attracted much attention for its frequency-invariant beampattern, high directivity factor and compact size. In this work, the design of differential beamformers with small inter-element spacing planar microphone arrays is concerned. In order to exactly control the main lobe beamwidth and sidelobe level and obtain minimum main lobe beamwidth with a given sidelobe level, we design the desired beampattern by applying the Chebyshev polynomials at first, via exploiting the structure of the frequency-independent beampattern of a theoretical Nth-order differential beamformer. Next, the so-called null constrained and least square beamformers, which can obtain approximately frequency-invariant beampattern at relatively low frequencies and can be steered to any direction without beampattern distortion, are proposed based on planar microphone arrays to approximate the designed desired beampatterns. Then, for dealing with the white noise amplification at low-frequency bands and beampattern divergence problems at high-frequency bands of the null constrained and least square beamformers, the so-called minimum norm and combined solutions are deduced, which can compromise among the white noise gain, directivity factor and beampattern distortion flexibly. Preliminary simulation results illustrate the properties and advantages of the proposed differential beamformers.

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

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

Improving Lateral Resolution in 3-D Imaging With Micro-beamforming Through Adaptive Beamforming by Deep Learning

There is an increased desire for miniature ultrasound probes with small apertures to provide volumetric images at high frame rates for in-body applications. Satisfying these increased requirements makes simultaneous achievement of a good lateral resolution a challenge. As micro-beamforming is often employed to reduce data rate and cable count to acceptable levels, receive processing methods that try to improve spatial resolution will have to compensate the introduced reduction in focusing. Existing beamformers do not realize sufficient improvement and/or have a computational cost that prohibits their use. Here we propose the use of adaptive beamforming by deep learning (ABLE) in combination with training targets generated by a large aperture array, which inherently has better lateral resolution. In addition, we modify ABLE to extend its receptive field across multiple voxels. We illustrate that this method improves lateral resolution both quantitatively and qualitatively, such that image quality is improved compared with that achieved by existing delay-and-sum, coherence factor, filtered-delay-multiplication-and-sum and Eigen-based minimum variance beamformers. We found that only in silica data are required to train the network, making the method easily implementable in practice.

Novel spatio-temporal non-linear beamformers for sparse synthetic aperture ultrasound imaging

The development of two modified non-linear beamformers, Spatio-Temporal Delay Multiply and Sum (ST-DMAS) and Spatio-Temporal Delay Euclidian-Weighted Multiply and Sum (ST-DewMAS) is reported in this paper. A sparse-transmit scheme (with only 8 transmits) on Synthetic Transmit Aperture technique (sparse STA) was chosen to evaluate the beamformers ability to generate the high-resolution Ultrasound image. These methods allow for obtaining superior-quality imaging at enhanced frame rates. The different beamformers of ST-DewMAS, ST-DMAS, Filtered Delay Multiply and Sum (F-DMAS), and Delay and Sum (DAS), were compared in terms of the Axial and Lateral Resolutions, AR and LR, respectively, Contrast-to-Noise Ratio (CNR), Contrast Ratio (CR), and Generalized CNR (GCNR). Experimental results demonstrate that the developed ST-DMAS and ST-DewMAS reconstruction on sparse STA technique resulted in better quality images compared to those obtained using DAS and F-DMAS. Specifically, the metrics of AR, LR CR, CNR, and GCNR showed improvements of more than 25% (for ST-DMAS) and 40 % (for ST-DewMAS) over those from DAS and F-DMAS beamformed images, respectively. Thus, the results demonstrate that the frame rate and image quality of an US system can both be enhanced by ST-DewMAS compared to the beamformers of F-DMAS and DAS.

Correlation-based modified delay-multiply-and-sum beamforming applied to medical ultrasound imaging

BACKGROUND AND OBJECTIVE

Recently, the Filtered Delay-Multiply-and-Sum (F-DMAS) beamformer was successfully applied to Ultrasound Imaging (UI), improving the image quality compared to the conventional data-independent Delay-and-Sum (DAS) beamformer. However, its reconstructed images lead to restricted resolution, contrast, and dark regions in the speckle. Various beamformers based on F-DMAS were proposed to mitigate these issues; some improved resolution and contrast at the expense of more dark regions; others reduced the dark points with lower contrast than the F-DMAS beamformer. This study aims to propose a novel beamformer, improving resolution and contrast while reducing dark points in the speckle.

METHODS

This study proposes a modified version of the F-DMAS beamformer, using two modifications to compensate for the aforesaid trade-off. Firstly, coupled signals' Correlation Coefficient (CC) was calculated and compared to a threshold value. The multiplications were applied only to the high-correlated (those whose CC is higher than the threshold value) signals. Secondly, a new Modified Coherence Factor (MCF) was applied to the high-correlated signals. Then, these two new beamformers were combined to reach a novel beamformer entitled "Modified DMAS (MDMAS)."

RESULTS

The performance of MDMAS was evaluated using simulating Point-Spread-Function, Cyst phantom, the experimental geabr dataset, and an in vivo dataset. Moreover, we evaluated the performance of the MDMAS beamformer quantitatively. Full-width-half-maximum (FWHM), contrast-ratio (CR), contrast-to-noise-ratio (CNR), speckle signal-to-noise-ratio (sSNR), and generalized-CNR (gCNR) were assessed.

CONCLUSIONS

This paper modified the conventional F-DMAS beamformer by adaptively multiplying signals. Then, CF was implemented on high correlated signals (MCF) and combined with the adaptive beamformer to compensate for the poor contrast. Results highlight that the MDMAS beamformer outperforms F-DMAS in terms of resolution and contrast without compromising the speckle from the dark region artifact.

3-D ultrasonic image reconstruction in frequency domain using a virtual transducer model

In ultrasonic non-destructive testing, image reconstruction is essential to restore the diffracted ultrasound signals to improve the lateral resolution of images. Some reconstruction methods, like DAS-based synthetic aperture imaging, are inefficient, especially for reconstructing three-dimensional (3-D) images. Other methods do not provide high-resolution results, because they neglect the distortion effect introduced by transducer geometry. To overcome these disadvantages, we propose a 3-D ultrasonic image reconstruction method based on synthetic aperture wavenumber algorithm. It considers wave diffraction and transducer geometry effects, and can refocus the reflectors even in non-focal zone, which suits for large depth range imaging. This method builds a virtual transducer model in frequency domain by treating the focused transducer as a virtual planar transducer on its focal plane. In addition, the method uses non-uniform fast Fourier transform and deconvolution operation to achieve the 3-D image reconstruction, which has remarkably improved the efficiency and accuracy. According to the experimental results, the lateral resolution of an image reconstructed by the proposed method can reach 290.2 μm, exceeding the lateral resolution limitation of the 15 MHz focused transducer (523.24 μm). Furthermore, the proposed method only takes 0.744 s to reconstruct a 3-D image with 1000×100×100 pixels, while the time domain SAFT takes about 1163.8 s. It shows the potential for real-time 3-D imaging under advanced hardware.

Feasibility of Electromagnetic Knee Imaging Verified on ex-vivo Pig Knees

OBJECTIVE

The potential of electromagnetic (EM) knee imaging system verified on ex-vivo pig knee joint as an essential step before clinical trials is demonstrated. The system, which includes an antenna array of eight printed biconical elements operating at the band 0.7-2.2 GHz, is portable and cost-effective. Importantly, it can provide daily monitoring and onsite real-time examinations imaging tool for knee injuries.

METHODS

Six healthy hind legs from three dead adult pigs were removed at the hip and suspended in the developed system. For each pig, the right- and left-knee were scanning sequentially. Then ligament tear was emulated by injecting distilled water into the left knee joint of each pig for early (5 mL water) and mid-stage (10 mL water) injuries. The injured left knees were re-scanned. A modified multi-static fast delay, multiply and sum algorithm (MS-FDMAS) is used to reconstruct imaging of the knee. All knees connective tissues, such as anterior and posterior cruciate ligaments (ACL, PCL), lateral and medial collateral ligaments (LCL, MCL), tendons, and meniscus, are extracted from a healthy hind leg along with collected synovial fluid. The extracted tissues and fluid were characterized and modelled as their data are not available in the literature, then imported to build an equivalent model for pig knee of 1 mm3 resolution in a realistic simulation environment.

RESULTS

The obtained results proved potential of the proposed system to detect ligament/tendon tears.

CONCLUSION

The proposed system has the potential to detect early knee injuries in a realistic environment.

SIGNIFICANCE

Contactless EM knee imaging system verified on ex-vivo pig joints confirms its potential to reconstruct knee images. This work lays the groundwork for clinical EM system for detecting and monitoring knee injuries.

Optimally-weighted non-linear beamformer for conventional focused beam ultrasound imaging systems

A novel non-linear beamforming method, namely, filtered delay optimally-weighted multiply and sum (F-DowMAS) beamforming is reported for conventional focused beamforming (CFB) technique. The performance of F-DowMAS was compared against delay and sum (DAS), filtered delay multiply and sum (F-DMAS), filtered delay weight multiply and sum (F-DwMAS) and filter delay Euclidian weighted multiply and sum (F-DewMAS) methods. Notably, in the proposed method the optimal adaptive weights are computed for each imaging point to compensate for the effects due to spatial variations in beam pattern in CFB technique. F-DowMAS, F-DMAS, and DAS were compared in terms of the resulting image quality metrics, Lateral resolution (LR), axial resolution (AR), contrast ratio (CR) and contrast-to-noise ratio (CNR), estimated from experiments on a commercially available tissue-mimicking phantom. The results demonstrate that F-DowMAS improved the AR by 57.04% and 46.95%, LR by 58.21% and 53.40%, CR by 67.35% and 39.25%, and CNR by 44.04% and 30.57% compared to those obtained using DAS and F-DMAS, respectively. Thus, it can be concluded that the newly proposed F-DowMAS outperforms DAS and F-DMAS. As an aside, we also show that the optimal weighting strategy can be extended to benefit DAS.

Nonlinear mechanisms in photoacoustics-Powerful tools in photoacoustic imaging

Many nonlinear effects have been discovered and developed in photoacoustic imaging. These nonlinear mechanisms have been explored for different utilizations, such as enhancing imaging contrast, measuring tissue temperature, achieving super-resolution imaging, enabling functional imaging, and extracting important physical parameters. This review aims to introduce different nonlinear mechanisms in photoacoustics, underline the fundamental principles, highlight their representative applications, and outline the occurrence conditions and applicable range of each nonlinear mechanism. Furthermore, this review thoroughly discusses the nonlinearity rule concerning how the mathematical structure of the nonlinear dependence is correlated to its practical applications. This summarization is useful for identifying and guiding the potential applications of nonlinearity based on their mathematical expressions, and is helpful for new nonlinear mechanism discovery or implementation in the future, which facilitates further breakthroughs in nonlinear photoacoustics.

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.

Weighted non-linear beamformers for low cost 2-element receive ultrasound imaging system

In this paper, the development of modified beamforming methods, Filtered Delay Weight Multiply and Sum (F-DwMAS) and Filtered Delay Euclidian-Weighted Multiply and Sum (F-DewMAS), are reported. These methods were investigated on a minimum-redundancy synthetic aperture technique, called as 2 element Receive Synthetic Aperture Focusing Technique (2R-SAFT), which uses one element on transmit and two consecutive elements on receive, for reducing hardware complexity without compromising much on the image quality. The performance of the developed F-DwMAS and F-DewMAS methods were compared with Delay and Sum (DAS) and recently introduced F-DMAS beamforming methods. Notably, in the proposed methods, an additional aperture window function is designed and incorporated to the F-DMAS method. The different methods of F-DwMAS, F-DewMAS, F-DMAS and DAS were compared in terms of the resulting image quality metrics, Lateral Resolution (LR), Axial Resolution (AR), Contrast Ratio (CR) and contrast-to-noise ratio (CNR), in simulation and experiments on tissue-mimicking phantoms. Experimental results show that (F-DwMAS) and {F-DewMAS} resulted in improvements of AR by (46.32% and 23.51%), {43.56% and 17.78%}, LR by (47.81% and 30.27%), {44.26% and 26.14%} and CR by (45.68% and 17.15%), {42.16% and 9.87%} compared to those obtained using DAS and F-DMAS, respectively. However, CNR of F-DwMAS and F-DewMAS was found to be 31.19% and 21.16% less compared to DAS, but 4.89% and 18.64% more than F-DMAS, respectively. Hence, it can be concluded that the image quality improved by both F-DwMAS and F-DewMAS compared to DAS and F-DMAS. Also, between F-DwMAS and F-DewMAS, the later has the advantage of ready applicability to different acquisition schemes and settings compared to the former also having an additional advantage of better CNR compared to both F-DMAS and F-DewMAS.

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.

A Low-complexity Minimum-variance Beamformer Based on Orthogonal Decomposition of the Compounded Subspace

Minimum-variance (MV) beamforming, as a typical adaptive beamforming method, has been widely studied in medical ultrasound imaging. This method achieves higher spatial resolution than traditional delay-and-sum (DAS) beamforming by minimizing the total output power while maintaining the desired signals. However, it suffers from high computational complexity due to the heavy calculation load when determining the inverse of the high-dimensional matrix. Low-complexity MV algorithms have been studied recently. In this study, we propose a novel MV beamformer based on orthogonal decomposition of the compounded subspace (CS) of the covariance matrix in synthetic aperture (SA) imaging, which aims to reduce the dimensions of the covariance matrix and therefore reduce the computational complexity. Multiwave spatial smoothing is applied to the echo signals for the accurate estimation of the covariance matrix, and adaptive weight vectors are calculated from the low-dimensional subspace of the original covariance matrix. We conducted simulation, experimental and in vivo studies to verify the performance of the proposed method. The results indicate that the proposed method performs well in maintaining the advantage of high spatial resolution and effectively reduces the computational complexity compared with the standard MV beamformer. In addition, the proposed method shows good robustness against sound velocity errors.

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

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

Nonlinear pth root spectral magnitude scaling beamforming for clinical photoacoustic and ultrasound imaging

A recently introduced nonlinear pth root delay-and-sum (NL-p-DAS) beamforming (BF) technique for ultrasound (US) and photoacoustic (PA) imaging, achieving better spatial and contrast resolution compared to a conventional delay and sum (DAS) technique. While the method is advantageous for better resolution, it suffers from grainy speckles and dark areas in the image mainly due to the interference of non-sinusoidal functions. In this Letter, we introduce a modified NL-p-DAS technique called nonlinear pth root spectral magnitude scaling (NL-p-SMS), which performs the pth root on the spectral magnitude instead of the temporal amplitude. We evaluated the US and PA images of NL-p-SMS against those of NL-p-DAS by comparing the axial and lateral line profiles, contrasts, and contrast-to-noise ratios (CNRs) in both phantom and in vivo imaging studies with various p values. As a result, we found that the NL-p-SMS has better axial resolution and CNR than the NL-p-DAS, and reduces the grainy speckles and dark area artifacts. We believe that, with this enhanced performance, our proposed approach could be an advancement compared to the existing nonlinear BF algorithms.

Incoherent Clutter Suppression Using Lag-One Coherence

The lag-one coherence (LOC), derived from the correlation between the nearest-neighbor channel signals, provides a reliable measure of clutter which, under certain assumptions, can be directly related to the signal-to-noise ratio of individual channel signals. This offers a direct means to decompose the beamsum output power into contributions from speckle and spatially incoherent noise originating from acoustic clutter and thermal noise. In this study, we applied a novel method called lag-one spatial coherence adaptive normalization (LoSCAN) to locally estimate and compensate for the contribution of spatially incoherent clutter from conventional delay-and-sum (DAS) images. Suppression of incoherent clutter by LoSCAN resulted in improved image quality without introducing many of the artifacts common to other adaptive imaging methods. In simulations with known targets and added channel noise, LoSCAN was shown to restore native contrast and increase DAS dynamic range by as much as 10-15 dB. These improvements were accompanied by DAS-like speckle texture along with reduced focal dependence and artifact compared with other adaptive methods. Under in vivo liver and fetal imaging conditions, LoSCAN resulted in increased generalized contrast-to-noise ratio (gCNR) in nearly all matched image pairs ( N = 366 ) with average increases of 0.01, 0.03, and 0.05 in good-, fair-, and poor-quality DAS images, respectively, and overall changes in gCNR from -0.01 to 0.20, contrast-to-noise ratio (CNR) from -0.05 to 0.34, contrast from -9.5 to -0.1 dB, and texture μ/σ from -0.37 to -0.001 relative to DAS.

A Mixed Transmitting-Receiving Beamformer With a Robust Generalized Coherence Factor: Enhanced Resolution and Contrast

Adaptive beamforming has been widely studied for ultrasound imaging over the past few decades. The minimum variance (MV) and generalized coherence factor (GCF) approaches have been validated as effective methods. However, the MV method had a limited contribution to contrast improvement, while the GCF method suffered from severe speckle distortion in previous studies. In this article, a novel ultrasound beamforming approach based on MV and GCF beamformers is proposed to enhance the spatial resolution and contrast in synthetic aperture (SA) ultrasound imaging. First, the MV optimization problem is conceptually redefined by minimizing the total power of the transmitting and receiving outputs. Estimation of the covariance matrices in transmit and receive apertures is carried out and then utilized to determine adaptive weighting vectors. Second, a data-compounding method, viewed as a spatial low-pass filter, is introduced to the GCF method to optimize the spatial spectrum of echo signals and obtain better performance. Robust principal component analysis (RPCA) processing is additionally employed to obtain the final output. Simulation, experimental, and in vivo studies are conducted on different data sets. Relative to the traditional delay-and-sum (DAS) beamformer, mean improvements in the full-width at half-maximum and contrast ratio of 89% and 94%, respectively, are achieved. Thus, considerable enhancement of the spatial resolution and contrast is obtained by the proposed method. Moreover, the proposed method performs better in terms of the computational complexity. In summary, the proposed scheme effectively enhances ultrasound imaging quality.

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

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

Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging

Beamformer is one of the most important components in ultrasound imaging system. The delay and sum (DAS) beamforming algorithm has been widely used in recent decades due to its simplicity and robustness. However, it has poor impact on resolution and contrast. A new beamformer named filtered delay multiply and sum (F-DMAS) which was an alternative of delay multiply and sum (DMAS) was proposed to overcome these shortcomings of DAS. Although F-DMAS partially enhances the image quality, its performance still has room for improvement. Therefore, a novel beamformer named lag-based delay multiply and sum (L-DMAS) which combines autocorrelation signals with DMAS algorithm is proposed by us to improve its efficiency. Field II was employed to synthesize a point target phantom and a cyst phantom to compare the performance between DAS, F-DMAS, double stage delay multiply and sum (DS-DMAS), and L-DMAS. We also estimate the performance of four algorithms on experimental data and in vivo data. These results show that both DS-DMAS and L-DMAS are better than DAS and F-DMAS in each case. In some cases, DS-DMAS and L-DMAS have little difference in performance, but in other cases, L-DMAS outperforms DS-DMAS. Graphical Abstract.

Two-Dimensional Spatial Coherence for Ultrasonic DMAS Beamforming in Multi-Angle Plane-Wave Imaging

Ultrasonic multi-angle plane-wave (PW) coherent compounding relies on delay-and-sum (DAS) beamforming of two-dimensional (2D) echo matrix in both the dimensions PW transmit angle and receiving channel to construct each image pixel. Due to the characteristics of DAS beamforming, PW coherent compounding may suffer from high image clutter when the number of transmit angles is kept low for ultrafast image acquisition. Delay-multiply-and-sum (DMAS) beamforming exploits the spatial coherence of the receiving aperture to suppress clutter interference. Previous attempts to introduce DMAS beamforming into multi-angle PW imaging has been reported but only in either dimension of the 2D echo matrix. In this study, a novel DMAS operation is proposed to extract the 2D spatial coherence of echo matrix for further improvement of image quality. The proposed 2D-DMAS method relies on a flexibly tunable p value to manipulate the signal coherence in the beamforming output. For p = 2.0 as an example, simulation results indicate that 2D-DMAS outperforms other one-dimensional DMAS methods by at least 9.3 dB in terms of ghost-artifact suppression. Experimental results also show that 2D-DMAS provides the highest improvement in lateral resolution by 32% and in image contrast by 15.6 dB relative to conventional 2D-DAS beamforming. Nonetheless, since 2D-DMAS emphasizes signal coherence more than its one-dimensional DMAS counterparts, it suffers from the most elevated speckle variation and the granular pattern in the tissue background.

Speckle coherence of piecewise-stationary stochastic targets

The van Cittert-Zernike (VCZ) theorem describes the propagation of spatial covariance from an incoherent source distribution, such as backscatter from stochastic targets in pulse-echo imaging. These stochastic targets are typically assumed statistically stationary and spatially incoherent with uniform scattering strength. In this work, the VCZ theorem is applied to a piecewise-stationary scattering model. Under this framework, the spatial covariance of the received echo data is demonstrated as the linear superposition of covariances from distinct spatial regions. This theory is analytically derived from fundamental physical principles, and validated through simulation studies demonstrating superposition and scaling. Simulations show that linearity is preserved over various depths and transmit apodizations, and in the presence of noise. These results provide a general framework to decompose spatial covariance into contributions from distinct regions of interest, which may be applied to advanced imaging methods. While the simulation tools used for validation are specific to ultrasound, this analysis is generally applicable to other coherent imaging applications involving stochastic targets. This covariance decomposition provides the physical basis for a recently described imaging method, Multi-covariate Imaging of Sub-resolution Targets.

Multi-covariate Imaging of Sub-resolution Targets

Conventional B-mode ultrasound imaging assumes that targets consist of collections of point scatterers. Diffraction, however, presents a fundamental limit on a scanner's ability to resolve individual scatterers in most clinical imaging environments. Well-known optics and ultrasound literature has characterized these diffuse scattering targets as spatially incoherent and statistically stationary. In this paper, we apply a piecewise-stationary statistical model to diffuse scattering targets, in which the covariance of backscattered echoes can be described as the linear superposition of constituent components corresponding to echoes from distinct spatial regions in the field. Using this framework, we present Multi-covariate Imaging of Sub-resolution Targets (MIST), a novel estimation-based method to image the statistical properties of diffuse scattering targets, based on a decomposition of aperture domain spatial covariance. The mathematical foundations of the estimator are analytically derived, and MIST is evaluated in phantom, simulation, and in vivo studies, demonstrating consistent improvements in contrast-to-noise ratio and speckle statistics across imaging targets, without an apparent loss in resolution.

Ultrasound Baseband Delay-Multiply-and-Sum (BB-DMAS) nonlinear beamforming

Compared to conventional Delay-and-Sum (DAS) beamforming, Delay-Multiply-and-Sum (DMAS) imaging uses multiplicative coupling of channel pairs for spatial coherence of receiving aperture to improve image resolution and contrast. However, present DMAS imaging is based on the radio-frequency (RF) channel signals (RF-DMAS) and thus requires large oversampling to avoid aliasing and switching of band-pass filtering to isolate the corresponding spectral components for imaging. Baseband DMAS (BB-DMAS) beamforming in this study is based on the demodulated channel signals to provide similar results but with simplified signal processing. The BB-DMAS beamforming scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase. After channel sum, the output dimensionality is restored by p-th power. The multiplicative coupling in BB-DMAS always renders baseband signal and thus the need for oversampling is eliminated. Besides, the BB-DMAS can use any rational p values to provide flexible image quality and an explicit relation between BB-DMAS beamforming and channel-domain phase coherence exists. Our results show that the image characteristics between BB-DMAS and RF-DMAS are similar. The suppression of lateral side lobe level, grating lobe level and uncorrelated random noises gradually increases with the rational p value in BB-DMAS beamforming. The image contrast improves from -24.8 dB in DAS to -34.3 dB, -43.0 dB and -51.4 dB in BB-DMAS, respectively with p value of 1.5, 2.0 and 2.5. In conclusion, BB-DMAS beamforming provides flexible manipulation of image quality by introducing baseband spatial coherence in the ultrasonic imaging.

Multi-line acquisition with delay multiply and sum beamforming in phased array ultrasound imaging, validation of simulation and in vitro

Increasing the frame rate of medical ultrasound imaging is very important, especially in applications such as cardiac diagnostic imaging, where such an imaging should be able to facilitate the examination of the temporal behaviour of the short cardiac cycle. Frame rate can be increased by the multi-line acquisition (MLA) method, also called parallel receive beamforming (PRB), where several beams are received from a single transmit (Tx) beam. The shortage is that imaging performance would be sacrificed. Filtered-delay multiply and sum (F-DMAS) is a non-linear beamforming technique proven to be able to improve the contrast and resolution of the image compared to traditional delay and sum (DAS) beamforming. In this paper, we proposed to combine MLA and the lower complexity F-DMAS algorithm, and use synthetic transmit beams (STB) to reduce the artifacts of MLA. The simulations of point targets and cyst phantoms were all carried out in Matlab using Field II. The results show that 2 line acquisition with delay multiply and sum (DMAS 2MLA) beamforming presents an equivalent imaging performance to that of traditional DMAS beamforming, and obtains a 7.69% higher resolution and 2 times higher contrast ratio in comparison to DAS beamforming. A real RF data experiment was applied to support the feasibility and validity of our method. The low complexity of F-DMAS (O(N)) would make it easy to implement 2 parallel beamformers. Thus, by combining 2MLA and F-DMAS, the frame rate can be improved to 2-fold higher with a better image quality compared to that of DAS beamforming.

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.

High-Resolution Fast Ultrasound Imaging With Adaptive-Lag Filtered Delay-Multiply-and-Sum Beamforming and Multiline Acquisition

Multiline acquisition (MLA) is a well-established method for a high-frame-rate cardiac ultrasound imaging, which is commonly used in conjunction with delay-and-sum (DAS) beamforming. The block-like artifacts that occur secondary to the use of MLA can be reduced using interpolation of the data acquired from adjacent transmitted beams-a method called synthetic transmit beamforming (STB). A recently proposed filtered delay-multiply-and-sum (F-DMAS) is a novel beamforming method, based on modified autocorrelation of the aperture data, which provides superior contrast resolution compared to the DAS beamforming. In this study, we demonstrate that a combination of the F-DMAS with the STB compensated MLA results in superior contrast as compared to both DAS beamformed STB and DAS beamformed single-line acquisition. Moreover, we propose a novel formulation for adaptive-lag F-DMAS that outperforms both DAS and F-DMAS in terms of contrast and lateral resolutions. The results are demonstrated in tissue-mimicking phantom and in human cardiac data.