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

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.

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

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

Improving lateral resolution and contrast by combining coherent plane-wave compounding with adaptive weighting for medical ultrasound imaging

Due to the severe lateral lobe artifact by coherent plane-wave compounding (CPWC) and the low signal-to-noise ratio of radiofrequency (RF) data collected from the plane wave, the adaptive beamforming methods based on focused wave imaging (FWI) are improper to be directly applied to CPWC. To obtain a high-quality image with high resolution and contrast, this study combined the threshold phase coherence factor (THR-PCF) with the reconstructed covariance matrix minimum variance (RCM-MV) and then proposed a novel CPWC-based adaptive beamforming algorithm, THR-PCF + RCM-MV. The simulation, phantom, and in-vivo experiments were performed to investigate the performance of the proposed methods in comparison with the CPWC and the classical adaptive methods including the minimum variance (MV), generalized coherence factor (GCF) and their combination GCF + MV. The simulation results demonstrated that the THR-PCF + RCM-MV beamformer improved contrast ratio (CR) by 28.14%, contrast noise ratio (CNR) by 22.01%, speckle signal-to-noise ratio (s_SNR) by 23.58%, generalized contrast-to-noise ratio (GCNR) by 0.3%, and the full width at half maximum (FWHM) by 43.38% on average, compared with the GCF + MV method. The phantom experimental results showed a better performance of the THR-PCF + RCM-MV beamformer with an average improvement by 21.95% in CR, 2.62% in s_SNR, and 48.64% in FWHM compared with the GCF + MV. Meanwhile, the results showed that the image quality of the near and far fields was enhanced by the THR-PCF + RCM-MV. The in-vivo imaging results showed that our new method had potential for clinical application. In conclusion, the lateral resolution and contrast of medical ultrasound imaging could be improved greatly with our proposed method.

Circular statistics vector for improving coherent plane wave compounding image in Fourier domain

In this work, a circular statistics vector (CSV) weighting Fourier domain (FD) beamforming for ultrasound plane-wave images was proposed to achieve better image quality with a high frame rate. Firstly, the cosine and sine components of the instantaneous phase are extracted from undelayed RF signals. Secondly, the FD beamformed cosine and sine components are used to establish the CSV. Finally, the FD beamformed amplitude image is weighted by the CSV. The resolution, contrast, and computation complexity were used to assess the performance of the proposed method. The results revealed that FD_CSV could significantly reduce the computational load compared to the conventional DAS_CSV on the equal improvement of image quality. Besides, compared to coherence factor (CF), phase coherence factor (PCF), etc., based on variance calculation, the CSV based on mean resultant vector calculation can effectively preserve the speckle due to the more tolerant to phase errors. The proposed FD_CSV weighting method has successfully conducted high image quality and low computational load.

Adaptive subarray coherence based post-filter using array gain in medical ultrasound imaging

This paper presents an adaptive subarray coherence-based post-filter (ASCBP) applied to the eigenspace-based forward-backward minimum variance (ESB-FBMV) beamformer to simultaneously improve image quality and beamformer robustness. Additionally, the ASCBP can separate close targets. The ASCBP uses an adaptive noise power weight based on the concept of the beamformer's array gain (AG) to suppress the noise adaptively and achieve improved images. Moreover, a square neighborhood average was applied to the ASCBP in order to provide more smoothed square neighborhood ASCBP (SN-ASCBP) values and improve the speckle quality. Through simulations of point phantoms and cyst phantoms and experimental validation, the performance of the proposed methods was compared to that of delay-and-sum (DAS), MV-based beamformers, and subarray coherence-based post-filter (SCBP). The simulated results demonstrated that the ASCBP method improved the full width at half maximum (FWHM) by 57 % and the coherent interference suppression power (CISP) by 52 dB compared to the SCBP post-filter. Considering the experimental results, the SN-ASCBP method presented the best enhancement in terms of generalized contrast to noise ratio (gCNR) and contrast ratio (CR) while the ASCBP showed the best improvement in FWHM among other methods. Furthermore, the proposed methods presented a striking performance in low SNRs. The results of evaluating the different methods under aberration and sound speed error illustrated the better robustness of the proposed methods in comparison with others.

Dual projection generalized sidelobe canceller based on mixed signal subspace for ultrasound imaging

In this paper, we propose a dual projection generalized sidelobe canceller (DPGSC) based on mixed subspace (MS) for ultrasound imaging, which aims to improve the speckle signal-noise-ratio (sSNR) and decrease the dark-region artifacts. A mixed signal subspace based on the correlation between the desired steering vector and the eigenvectors is constructed to further optimize the desired steering vector and the final weight vector. The simulated and experimental results show that the proposed method can greatly improve the speckle uniformity. In the geabr_0 experiment, the standard deviation of background and sSNR of MS-DPGSC can be improved by 48.07% and 58.49% more than those of eigenspace-based generalized sidelobe canceller (ESGSC). Furthermore, for a hyperechoic target, the maximal improvement of contrast ratio is 95.29%. In terms of anechoic cyst, the contrast-to-noise ratio of MS-DPGSC is increased by 123.08% than that of ESGSC. The rat mammary tumor experimental data show that the proposed method has better comprehensive imaging effect than traditional generalized sidelobe cancellers and ESGSCs.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

A submatrix spatial coherence approach to minimum variance beamforming combined with sign coherence factor for coherent plane wave compounding

BACKGROUND:

The coherent plane wave compounding (CPWC) is a promising technique to enhance the imaging quality while maintaining the high frame rate in the plane wave ultrasound imaging. Recently, the spatial-coherence-based method has been specially designed to process echo matrix required by the minimum variance (MV) method.

OBJECTIVE:

In this paper, a novel beamforming method that integrates the submatrix-spatial-coherence-based MV with the sign coherence factor (SCF) is proposed to further improve the imaging quality.

METHOD:

The submatrix smoothing technique is modified to smooth and de-correlate signals of the receiving array dimension. Then, the SCF is used to modify the input vector of the beamformer, which can reduce side lobe noises with almost no increase in the amount of calculation. Simulation, phantom, in vivo, and sound velocity error experiments have been performed to verify the superiority of the proposed beamformer.

RESULTS:

The imaging results show that the proposed approach performs better in the imaging resolution and contrast compared to the traditional CPWC method.

CONCLUSION:

The robustness of the proposed method is enhanced, and the over-suppression phenomenon can be alleviated, which is a phenomenon that occurs in the original spatial-coherence and SCF methods.

Covariance Matrix-Based Statistical Beamforming for Medical Ultrasound Imaging

Medical ultrasound image quality is often limited by clutter, which is the dominant mechanism of image degradation. A variety of beamforming methods have been extensively studied to reduce clutter and, thus, enhance ultrasound image quality. This article introduces a new beamforming approach, called covariance matrix-based statistical beamforming (CMSB), to improve the image contrast and preserve the background speckle pattern while simultaneously achieving a high-resolution performance. In CMSB, adaptive selection of subarray length, diagonal reducing, and mean-to-standard-deviation ratio-based subarray averaging are inherently combined to differentiate and reduce off-axis energy effectively. Moreover, rotary averaging prior to diagonal reducing is introduced to preserve speckle statistics. Simulated, experimental, and in vivo datasets were used to evaluate the imaging performance of the proposed method. The quantitative results indicate that, compared with delay-and-sum (DAS) beamforming, CMSB leads to average improvements of 44.5% and 97.3% in lateral resolution and contrast, respectively, in phantom experiments. Our work shows that CMSB is capable of improving image resolution and contrast while maintaining the speckle reliably. Preliminary in vivo study also demonstrates that the CMSB can enhance image contrast and lesion detection.

United Wiener postfilter for plane wave compounding ultrasound imaging

Plane wave compounding (PWC) is a valid method for ultrafast ultrasound imaging. Its imaging quality depends on the beamforming method. The coherence factor (CF) and Wiener postfilter are effective signal processing schemes for aberration correction. However, the CF usually causes over-suppression and brings artifacts. Additionally, the conventional CF and Wiener postfilter cannot fully utilize the spatial coherence in the PWC, which limits the imaging performance and increases the computation. In this paper, we propose a united Wiener postfilter specially for the PWC. The signal and noise power are both estimated through the echo signal matrix, rather than array signal vectors. The method also accords with the theoretical relationship between the CF and Wiener. To evaluate the performance of the proposed method, we conduct simulations, phantom and in vivo experiments and make comparisons with the delay-and-sum (DAS), the CF, the generalized coherence factor (GCF), the conventional Wiener and the scaled Wiener beamformers. Results indicate that our method can offer the better resolution and contrast than the DAS and Wiener. It also solves the over-suppression drawback of the CF. Specifically, the contrast ratio and contrast-to-noise ratio achieve 26.7% and 25.2% improvements in simulations, 28.7% and 32.4% in phantom experiments, respectively. The proposed method also performs well in terms of the speckle signal-to-noise ratio and the generalized contrast-to-noise ratio. Consequently, we believe that the proposed method is effective in enhancing the imaging quality of the PWC.

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

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

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

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

Multi-Operator Minimum Variance Adaptive Beamforming Algorithms Accelerated With GPU

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

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.

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.