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.

An adaptive beamformer based on dynamic phase coherence factor for pixel-based medical ultrasound imaging.

BACKGROUND: Pixel-based beamforming realizes dynamic focusing at the pixel level with a focused beam by assuming that the received signals are composed of spherical pulses. Far-focused pixel-based (FPB) imaging was proposed to avoid artifacts around the focal depth. However, the contrast improvement is limited. OBJECTIVE: We propose an adaptive weighting method based on dynamic phase coherence factor (DPCF) to improve the image contrast while preserving the speckle pattern. METHODS: The phase variation is dynamically estimated based on the noise energy proportion of echo signals and it is used to calculate phase coherence weights for suppressing interference and preserving desired signals. A depth-dependent parameter is designed for DPCF to enhance the performance of noise and clutter suppression in the far-field region. We further use the subarray averaging technique to smooth the speckle texture. RESULTS: The proposed method was evaluated on simulated, phantom experimental, and in vivo data. Results show that, compared with the phase coherence factor (PCF) based method, DPCF respectively leads to average CR improvements by more than 60% and 24% in simulation and experiment, while obtaining an improved speckle signal-to-noise ratio. CONCLUSIONS: The proposed method is a potentially valuable approach to obtaining high-quality ultrasound images in clinical applications.

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.

High-Quality Ultrafast Power Doppler Imaging Based on Spatial Angular Coherence Factor.

The morphological and hemodynamic changes of microvessels are demonstrated to be related to the diseased conditions in tissues. Ultrafast power Doppler imaging (uPDI) is a novel modality with a significantly increased Doppler sensitivity, benefiting from the ultrahigh frame rate plane-wave imaging (PWI) and advanced clutter filtering. However, unfocused plane-wave transmission often leads to a low imaging quality, which degrades the subsequent microvascular visualization in power Doppler imaging. Coherence factor (CF)-based adaptive beamformers have been widely studied in conventional B-mode imaging. In this study, we propose a spatial and angular coherence factor (SACF) beamformer for improved uPDI (SACF-uPDI) by calculating the spatial CF across apertures and the angular CF across transmit angles, respectively. To identify the superiority of SACF-uPDI, simulations, in vivo contrast-enhanced rat kidney, and in vivo contrast-free human neonatal brain studies were conducted. Results demonstrate that SACF-uPDI can effectively enhance contrast and resolution and suppress background noise simultaneously, compared with conventional uPDI methods based on delay-and-sum (DAS) (DAS-uPDI) and CF (CF-uPDI). In the simulations, SACF-uPDI can improve the lateral and axial resolutions compared with those of DAS-uPDI, from 176 to [Formula: see text] of lateral resolution, and from 111 to [Formula: see text] of axial resolution. In the in vivo contrast-enhanced experiments, SACF achieves 15.14- and 5.6-dB higher contrast-to-noise ratio (CNR), 15.25- and 3.68-dB lower noise power, and 240- and 15- [Formula: see text] narrower full-width at half-maximum (FWHM) than DAS-uPDI and CF-uPDI, respectively. In the in vivo contrast-free experiments, SACF achieves 6.11- and 1.09-dB higher CNR, 11.93- and 4.01-dB lower noise power, and 528- and 160- [Formula: see text] narrower FWHM than DAS-uPDI and CF-uPDI, respectively. In conclusion, the proposed SACF-uPDI method can efficiently improve the microvascular imaging quality and has the potential to facilitate clinical applications.

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.

Adaptive scaled coherence factor for ultrasound pixel-based beamforming.

Synthetic aperture (SA) ultrasound imaging can obtain images with high-resolution owing to its ability to dynamically focus in both directions. The signal-to-noise ratio (SNR) of SA imaging is poor because the pulse energy using one array element is quite low. Thus, the SA method with bidirectional pixel-based focusing (SA-BiPBF) was previously proposed as a solution to this challenge. However, using the nonadaptive delay-and-sum (DAS) beamforming still limits its imaging performance. This study proposes an adaptive scaled coherence factor (AscCF) for SA-BiPBF to further boost the image quality. The AscCF exploits generalized coherence factor (GCF) to measure the signal coherence to adaptively adapt the parameters in SNR estimation rather than fixed ones. Comparisons were made with several other weighting techniques by performing simulations and experiments for performance evaluation. Results confirm that AscCF applied to SA-BiPBF offers a good image contrast while reservation of the speckle pattern. AscCF achieves maximal improvements of contrast ratio (CR) by 48.5% and 47.76 % compared with scaled coherence factor (scCF), respectively in simulation and experiment. Simultaneously, the maximum of improvements in speckle signal-to-noise ratio (sSNR) of AscCF are 11.28 % and 20.01 % upon scCF in simulation and experiment, respectively. From the in vivo result, it also appears a potential for AscCF to act in clinical situations to better detect lesion and retain speckle pattern.

Novel Method for Fetal and Maternal Heart Rate Measurements Using 2-D Ultrasound Color Doppler Flow Images.

Fetal heart rate (FHR) and maternal heart rate (MHR) are important indicators of fetal well-being during pregnancy. A common method in clinical examination is to estimate the FHR using the Doppler shift of echoes from umbilical artery blood flow based on an ultrasound pulsed-wave (PW) Doppler technique. Similarly, a sampling gate can be located at the maternal blood flow to measure MHR using PW Doppler. Ultrasound color Doppler flow imaging (CDFI) is one of the most commonly used imaging modes for clinical fetal examinations. Color coding is employed to display the blood flow velocity and direction in color grades according to the Doppler shift. Continuous CDF images contain dynamic changes characteristics of the blood flow. The periodic characteristics can be used to obtain heart rate information. Therefore, here we propose a novel method to measure FHR and MHR simultaneously using CDF images. The proposed method calculates the histogram of color similarity of CDF images to initially extract the periodic characteristics of the CDF image sequence. The histogram of color similarity function is then processed by a bandpass filter and autocorrelation operation to reduce noise and enhance periodicity. Finally, peak detection is performed on the processed signal to obtain the period and estimate the heart rate. The proposed method can measure the FHR and MHR in parallel after selecting two regions containing the umbilical artery and maternal blood flow, respectively. Thus, the method has high computational efficiency. The proposed method was evaluated on a Doppler flow phantom and clinical CDF images and then compared with the PW Doppler method. The correlation analysis and Bland-Altman plots reveal that the proposed method agrees well with the PW Doppler. It is a sanity check method for real-time clinical FHR and MHR measurements.

Ultrasound far-focused pixel-based imaging using Wiener postfilter scaled by adjustable zero-cross factor.

Synthetic aperture (SA) imaging can provide a uniform lateral resolution but an insufficient signal-to-noise ratio (SNR). SA method with bidirectional pixel-based focusing (SA-BiPBF) has the ability to obtain a higher quality image than conventional SA imaging. In this paper, an enhanced SA-BiPBF named full aperture received far-focused pixel-based (FrFPB) is firstly proposed to obtain a high resolution image. An adjustable zero-cross factor scaled Wiener postfilter (AZFsW) is then implemented in FrFPB for improving contrast ratio (CR). The adjustable zero-cross factor is calculated using the polarity of echo signals sequence with an adjustable coefficient σ to estimate the signal coherence, and it is combined with Wiener postfilter to obtain a good capability of noise reduction and background speckle pattern preservation. Simulation and experiments have been conducted to evaluate the imaging performance of the proposed methods. Results show that FrFPB can obviously improve the resolution in comparison with SA-BiPBF, and contrast-to-noise ratio (CNR) and speckle signal-to-noise ratio (sSNR) are retained. In addition, AZFsW can achieve a much higher CR than SA-BiPBF. When σ is 0.6, the CR improvement is 96.7% in simulation, 78.7% in phantom experiment, and 49.2% in in-vivo experiment. To evaluate the imaging performance of AZFsW, coherence factor, conventional Wiener postfilter, and scaled Wiener postfilter are implemented. The imaging results show that when σ is in the range of [0.6, 0.7], AZFsW exhibits a satisfying comprehensive imaging performance.

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.

Adaptive scaling Wiener postfilter using generalized coherence factor for coherent plane-wave compounding.

This paper proposes an adaptive scaling Wiener postfilter (AScW) for coherent plane-wave compounding (CPWC) to improve the image quality. AScW introduces an adaptive scale factor dependent on the signal incoherence to maintain the performance balance between good noise suppression and good robustness. AScW utilizes several plane waves with a small angular difference to calculate generalized coherence factor (GCF) for the estimation of signal incoherence and noise power. And a standard depth parameter is used to further adjust the beamforming performance of AScW and improve speckle quality. The proposed method was tested on datasets acquired from simulation, experimental phantom and in-vivo study provided by the Plane-wave Imaging Challenge in Medical Ultrasound (PICMUS). Results show that AScW applied to CPWC can provide a good speckle quality and lateral resolution, while attaining a satisfying contrast. AScW can achieve maximal improvements of speckle signal-to-noise ratio (sSNR) by 36.4% (simulation) and 44.8% (experiment) compared with GCF, while 14.4% (simulation) and 12.5% (experiment) compared with the scaled Wiener postfilter (ScW). And the maximal lateral full width at half maximum (FWHM) improvements are 51.9% upon GCF and 53.7% upon ScW. Meanwhile, the contrast of AScW is comparable to that of GCF. From the results of in-vivo study, AScW also shows its clinical application potential for the visualization of anatomical structures and hyper echoic structures in ultrasound imaging.

An adaptive imaging method for ultrasound coherent plane-wave compounding based on the subarray zero-cross factor.

Coherent plane-wave compounding (CPWC) has the ability to generate high quality image using the backscattered signals from plane wave emitting at different steer angles. To improve the image quality of CPWC, adaptive weighting techniques have been introduced in the compounding procedure. This paper proposes subarray zeros-cross factor (SZF) for CPWC, and it is used as an adaptive weighting factor to improve image quality. The SZF is calculated based on polarity of plane-wave imaging results with adjacent steering angle to estimate the coherence of plane wave emitting events. It is effective to suppress noise and maintain background speckle pattern. Simulations and experiments were conducted to evaluate the performance of the proposed method. Results demonstrate that the SZF can achieve better performance on contrast ratio (CR) and resolution than traditional CPWC. For simulated cysts, a maximal CR improvement of 125.4% is achieved. For experimental cysts, the maximal CR improvement is 197.9%. Compared with coherence factor (CF) and generalized coherence factor (GCF), SZF can obtain improvements in contrast-to-noise ratio and speckle signal-to-noise ratio at near field and increase CR at far field. In addition, when subarray length L is in the range of [10,12], SZF can obtain satisfying comprehensive performance.

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

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

Dynamic coherence factor based on the standard deviation for coherent plane-wave compounding.

The ultrafast imaging technique based on plane wave transmission has been a commonly investigated imaging mode in medical ultrasound imaging. Coherent plane-wave compounding (CPWC) was proposed to improve the quality of plane-wave imaging (PWI), which obtained a high-quality image by summing the low-quality images formed by transmitting plane waves at different steering angles. Coherence factor (CF) weighting algorithms can effectively improve image contrast with low computational complexity. However, this usually introduces black artifacts and degraded speckle quality. In this paper, we propose a dynamic coherence factor (DCF) that is based on the angular difference of CPWC to adaptively determine the number of plane waves and utilizes several plane waves with small angular difference to evaluate coherence. To improve resolution and contrast-to-noise ratio (CNR), adjusted DCF (ADCF) introduces a parameter related to the standard deviation to adjust DCF. Furthermore, a square neighborhood ADCF (SN-ADCF) using a 2-dimensional average filter is designed to obtain higher contrast and speckle quality. The simulated, experimental and in-vivo datasets are used to evaluate the proposed methods. Results show that, in comparison with CF, DCF can achieve improved contrast ratio (CR), CNR and speckle signal-to-noise ratio (sSNR). ADCF achieves a maximal lateral full width at half maximum (FWHM) improvement by 40% and better speckle quality than CF. SN-ADCF causes about 20% improvements upon CF in CNR and sSNR, while maintaining a similar resolution performance. SN-ADCF also provides higher lateral resolution than the generalized coherence factor (GCF) and scaled coherence factor (scCF), meanwhile obtaining a comparable contrast and speckle quality. Therefore, SN-ADCF has a satisfying comprehensive performance, which can achieve a reasonable balance among resolution, contrast and speckle quality.

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

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

Short-lag spatial coherence combined with eigenspace-based minimum variance beamformer for synthetic aperture ultrasound imaging.

Recently, short-lag spatial coherence (SLSC) imaging has been widely studied to improve image contrast and contrast-to-noise ratio (CNR) in ultrasound imaging. Nevertheless, SLSC is unable to provide a good imaging resolution. Eigenspace-based minimum variance (ESBMV) beamformer was previously devised to promote imaging resolution, while enhancing imaging contrast. However, ESBMV will cause black-spot artifact problem under a high threshold of eigenvalues. Given their complementary properties, in this study, we propose an imaging method with synthetic aperture (SA) ultrasound imaging by combining SLSC weighting (SLSCw) and ESBMV, to improve imaging quality at all depth. Based on the spatial coherence of different sources, adaptive threshold of eigenvalues is designed for ESBMV. In the proposed method, receive aperture data are directly summed to get the receive aperture synthesized data, and then SLSC and ESBMV are applied in transmit aperture based on the receive synthesized data. After that, the estimated SLSC value is adopted as a weighting factor for ESBMV beamforming output. We demonstrate the performance of the proposed method based on simulated and experimental data. The results show that the proposed method can not only achieve satisfactory improvement in resolution and contrast but also remove the black-spot artifacts.