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Purpose: Beamforming using the generalized coherence factor (GCF) reduces sidelobe artifacts and provides an excellent contrast-to-noise ratio. We previously proposed GCFreal, a method to calculate GCF without generating analytic signals, and GCFbin, a method to calculate GCF by binarizing the received signals. In this study, we applied these methods to in vivo data and showed the effect of the computational complexity reduction on contrast performance. Methods: Channel RF data were acquired from the human liver and gallbladder. We set up several observation points in each data set and investigated the mechanism that causes the differences in contrast performance among the methods based on the signals and their power spectra in the channel direction. Results: For GCF and GCFreal, the obtained values were almost the same. However, there were large differences in GCFbin from GCF when the signals from the focus point or from outside the focus point were received on different channels. This is because the amplitudes of the signals with high coherence and those with low coherence were changed by binarizing the signals. Conclusion: While GCFbin can significantly reduce the computational complexity, there are differences in the values of GCFbin and GCF due to binarizing of the received signals. However, this difference resulted in GCFbin being superior to GCF in terms of artifact reduction. This is owing to the elimination of amplitude information in GCFbin, which makes it a new efficient coherence factor with different characteristics from GCF. [ABSTRACT FROM AUTHOR]

Purpose: In coherence-based beamforming (CBB) using a generalized coherence factor (GCF), unnecessary signals caused by sidelobes are reduced, and an excellent contrast-to-noise ratio (CNR) is achieved in ultrasound imaging. However, the GCF computation is complex compared to the standard delay-and-sum (DAS) beamforming. In the present study, we propose a method that significantly reduces the number of GCF computations. Methods: In the previously proposed GCFreal, generation of the analytic signal for each element in the conventional GCF could be omitted. Furthermore, in GCF estimated from binarized signals (GCFB) proposed in the present study, the GCF value is calculated after the received signal of each element is binarized to reduce the computational complexity of the GCF. Results: The values of GCFB and GCFreal estimated from simulation and experimental data were compared. We also evaluated the image quality of B-mode images weighted by GCFB and GCFreal. Compared with GCFreal, GCFB was superior in reducing unnecessary signals but tended to reduce the brightness of the diffused scattering media. The CNR improvement was comparable for both methods. Conclusion: Generalized coherence factor estimated from binarized signals exhibits excellent CNR improvement compared to DAS. CNR improvements yielded by GCFB and GCFreal may depend on the observation target; however, under the conditions of the present study, comparable performances were obtained. Because GCFB can significantly reduce the computational complexity, it is potentially applicable in clinical diagnostic equipment. [ABSTRACT FROM AUTHOR]

Purpose: The generalized coherence factor (GCF), an adaptive beamforming technique, can reduce unnecessary signals from an unfocused position without reducing the contrast-to-noise ratio. However, the computational complexity of this method is large compared to the conventional delay-and-sum (DAS) beamformer. In the present paper, we propose a novel method to achieve the same reduction effect of unnecessary signals with a smaller computational load than that of the conventional GCF approach. Methods: One of the factors increasing the computational complexity of the GCF-based beamformer compared with DAS is the generation of analytic signals at receiving elements. We clarified the mechanism of generating unnecessary signal components to enable the calculation of the GCF value directly from real signals without generating analytic signals. Furthermore, we proposed a method to filter out these components without generating analytic signals. Results: The GCF values obtained using the proposed and conventional methods were compared and verified using the actual data acquired from a phantom with an ultrasound diagnostic system. We also compared the B-mode images. As a result, equivalent GCF values and similar B-mode image quality were achieved with the proposed method with reduced computational complexity. Conclusion: With the proposed method, generation of analytic signals at receiving elements can be omitted, and as a result, the computational load of the GCF method can be greatly reduced, while preserving the effect of reducing unnecessary signals like with the conventional method. [ABSTRACT FROM AUTHOR]

Handheld ultrasound devices have been widely used for diagnostic applications. The use of the acoustic-field beamforming (AFB) method has been proposed for handheld ultrasound to reduce electricity consumption and avoid battery and unwanted heat issues. However, the image quality, such as the contrast ratio and contrast-to-noise-ratio, are poorer with this technique than with the conventional delay-and-sum method. To address the problems associated with the worse image quality in AFB imaging, in this paper we propose the use of an AFB-based generalized coherence factor (GCF) technique, in which the GCF weighting developed for adaptive beamforming is extended to AFB. Simulation data, experimental results, and in vivo testing verified the efficacy of our proposed AFB-based GCF technique.

Coherent plane-wave compounding (CPWC) is an effective method to improve the image quality of ultrasound plane-wave imaging (PWI), which coherently sums the delay-and-sum (DAS) beamforming outputs of PWI at different steering angles. However, due to the data-independent nature, the DAS obtains limited imaging resolution and contrast. Therefore, various adaptive beamforming methods have been presented to achieve improved imaging quality. In this paper, an adaptive weighting factor named normalized autocorrelation factor (NAF), which is derived by the normalized autocorrelation function (NACF), is proposed for CPWC. Simulated and experimental data provided by the plane wave imaging challenge in medical ultrasound organizers are used to evaluate the proposed method. Results show that the NAF-weighted CPWC can achieve an improved imaging quality in terms of lateral resolution, contrast ratio (CR), and contrast-to-noise ratio. In simulated images, the maximum improvements of the lateral full width at half maximum and CR are 60.3% and 29.7%, respectively. For experimental images, the corresponding improvements are 32.1% and 23.3%. The NAF is also compared with the generalized coherence factor (GCF) and short-lag spatial coherence (SLSC), and the simulation and phantom experimental results show that the NAF can get better lateral resolution and speckle signal-to-noise ratio (sSNR). For in-vivo data, the NAF shows distinct advantages over GCF and SLSC in preserving anatomical structures so as to get better CR, CNR, and sSNR. In addition, with a low computational complexity and load, the proposed method has potential to be applied to ultrafast ultrasound imaging for high quality images.

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 $R^{2}\text {-adj}=0.88$ in simulated data and $R^{2}\text {-adj}=0.98$ 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. [ABSTRACT FROM AUTHOR]

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.

Background Generalized coherence factor (GCF) can be adaptively estimated from channel data to suppress sidelobe artifacts. Conventionally, Fast Fourier Transform (FFT) is utilized to calculate the full channel spectrum and suffers from high computation load. In this work, autocorrelation (AR)-based algorithm is utilized to provide the spectral parameters of channel data for GCF estimation with reduced complexity. Methods Autocorrelation relies on the phase difference among neighboring channel pairs to estimate the mean frequency and bandwidth of channel spectrum. Based on these two parameters, the spectral power within the defined range of main lobe direction can be analytically computed from a pseudo spectrum with the presumed shape as the GCF weighting value. A bandwidth factor Q can be further included in the formulation of pseudo channel spectrum to optimize the performance. Results While the GCF computation complexity of a N -channel system reduces from O( N log 2 N ) with FFT to O( N ) with AR, the lateral side-lobe level is effectively suppressed in the GCF-AR method. In B-mode speckle imaging, the GCF-AR method can provide a higher image contrast together with a relatively low speckle variation. The resultant Contrast-to-Noise Ratio (CNR) improves from 6.7 with GCF-FFT method to 9.0 with GCF-AR method. Conclusion GCF-AR method reduces the computation complexity of adaptive imaging while providing superior image quality. GCF-AR method is more resistant to the speckle black-region artifacts near strong reflectors and thus improves the overall image contrast. [ABSTRACT FROM AUTHOR]

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., Competing Interests: Declaration of competing interest We declare that we have no financial and personal relationships with other people or organizations. None of the authors have a conflict of interest., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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. [ABSTRACT FROM AUTHOR]