DMAS Beamforming with Complementary Subset Transmit for Ultrasound Coherence-Based Power Doppler Detection in Multi-Angle Plane-Wave Imaging

Abstract

Conventional ultrasonic coherent plane-wave (PW) compounding corresponds to Delay-and-Sum (DAS) beamforming of low-resolution images from distinct PW transmit angles. Nonetheless, the trade-off between the level of clutter artifacts and the number of PW transmit angle may compromise the image quality in ultrafast acquisition. Delay-Multiply-and-Sum (DMAS) beamforming in the dimension of PW transmit angle is capable of suppressing clutter interference and is readily compatible with the conventional method. In DMAS, a tunable p value is used to modulate the signal coherence estimated from the low-resolution images to produce the final high-resolution output and does not require huge memory allocation to record all the received channel data in multi-angle PW imaging. In this study, DMAS beamforming is used to construct a novel coherence-based power Doppler detection together with the complementary subset transmit (CST) technique to further reduce the noise level. For p = 2.0 as an example, simulation results indicate that the DMAS beamforming alone can improve the Doppler SNR by 8.2 dB compared to DAS counterpart. Another 6-dB increase in Doppler SNR can be further obtained when the CST technique is combined with DMAS beamforming with sufficient ensemble averaging. The CST technique can also be performed with DAS beamforming, though the improvement in Doppler SNR and CNR is relatively minor. Experimental results also agree with the simulations. Nonetheless, since the DMAS beamforming involves multiplicative operation, clutter filtering in the ensemble direction has to be performed on the low-resolution images before DMAS to remove the stationary tissue without coupling from the flow signal.

Ultrasound Ultrafast Power Doppler Imaging with High Signal-to-Noise Ratio by Temporal Multiply-and-Sum (TMAS) Autocorrelation

“…The proposed TMAS power Doppler estimation may be applicable to not only DAS beamforming as demonstrated in this work, but also other adaptive beamforming methods. For example, when the TMAS power Doppler estimation is combined with any beamforming, which exploits the spatial coherence of blood flow signal in either the dimension of the receiving channel or the PW transmit angles such as in [ 16 , 17 , 19 , 20 , 24 , 25 , 26 ], the corresponding power Doppler imaging would rely on the spatial–temporal coherence of the blood flow signal to produce the image pixel. In this case, a smaller pt value may be used in a TMAS algorithm to alleviate the signal decorrelation of high-velocity blood flow, while the overall noise suppression remains unchanged due to the inclusion of spatial coherence in the beamforming stage.…”

“…Several beamforming methods have been proposed to reduce the noise level of power Doppler imaging in PW imaging by extracting the signal coherence in the spatial direction. For example, the coherent flow power Doppler (CFPD) method [ 16 , 17 ] relies on short-lag spatial coherence [ 18 ] to extract the coherence of the blood flow signal in the dimension of the receiving channel, while the Delay Multiply-and-Sum (DMAS) beamforming one is used to highlight the coherence of blood flow signal in the dimension of the PW transmit angles [ 19 , 20 ]. Note that, although the original DMAS beamforming method is implemented by simply multiplying the received echoes between every possible pair [ 21 ], alternative high-order versions of DMAS beamforming have been recently proposed to improve the computational efficiency and the flexibility of the tunable image quality [ 22 , 23 ].…”

“…For example, when a rational p value is used to represent the order of the signal coherence in DMAS beamforming, the efficient DMAS beamforming can be implemented by magnitude scaling of the echoes by p -th root and then, taking the p -th power of the coherently summed output. In addition to these coherence-based methods, the noise level in power Doppler imaging can also be significantly reduced by the cross-correlation of two complementary subsets of either the receiving channels or the PW transmit angles in the beamforming process [ 19 , 24 , 25 , 26 ]. Spatial–temporal denoising of the Doppler image sequence using the non-local mean filter is also proposed to produce a low-noise power Doppler estimation [ 27 ].…”

Noise Reduction Using Singular Value Decomposition with Jensen–Shannon Divergence for Coronary Computed Tomography Angiography

“…Noise reduction by SVD is performed by selecting an appropriate number of ranks k to estimate e in Equation ( 1 ). Various methods have been proposed for selecting the number of the rank [ 27 , 28 , 29 , 30 ]. However, in this study, the number of ranks that minimized the JS–divergence between the noise-free image and the noisy image was selected as the optimal number of ranks for denoising.…”

Resolution of the Ultrasound Doppler System Using Coherent Plane-Wave Compounding Technique

“…The effect of the influence of the ultrasound scatterers motion on the Doppler signal correlation function was theoretically investigated in [28], and in [23,29] a motion correction scheme, which allowed to improve the accuracy of the velocity estimation, as well as to improve the signal-to-noise ratio, was developed. A number of experimental works are devoted to the development of new techniques within the frame of the plane-wave compounding technique, which allow improving the image quality in terms of lateral resolution, contrast ratio, and contrast-to-noise ratio both for two-dimensional B-mode (brightness mode) images [30][31][32][33][34] and for Doppler techniques [35][36][37].…”