User Parameter-Free Minimum Variance Beamformer in Medical Ultrasound Imaging

Synthetic Aperture Ultrasound Imaging through Adaptive Integrated Transmitting-Receiving Beamformer

Synthetic aperture (SA) technique is very attractive for ultrafast ultrasound imaging, as the entire medium can be insonified by a single emission. It also permits applying the dynamic focusing as well as adaptive beamforming both in transmission and reception, which results in an enhanced image. In this paper, we firstly show that the problem of designing the transmit and receive beamformers in SA structure can be formulated as a problem of designing a one-way beamformer on a virtual array with a lateral response equal to that of the two-way beamformer on SA. It is also demonstrated that the length of the virtual aperture is increased to the sum of the transmit aperture length and the receive one, which can result in an enhanced resolution. Moreover, a better estimation of the covariance matrix can be obtained which can be utilized for applying adaptive minimum variance (MV) beamforming method on the virtual array, and consequently the resolution and contrast properties would be enhanced. The performance of the new method is compared with other existing MV-based methods and is quantified by some metrics such as the full width at half maximum (FWHM) and generalized contrast to noise ratio (GCNR). Our validations on simulations and experimental data have shown that the new method is capable of obtaining higher GCNR values while retaining or decreasing FWHM values almost all the time. Moreover, for the same subarray length for estimating the covariance matrices, the computational burden of the new method is significantly lower than those of the existing rival methods.

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.

Combining ADMIRE and MV to Improve Image Quality

Aperture domain model image reconstruction (ADMIRE) is a frequency-domain, model-based beamformer, in part designed for removing reverberation and off-axis clutter. Minimum variance (MV) is alternatively designed to reduce off-axis interference and improve lateral resolution. MV is known to be less effective in high incoherent noise scenarios, and its performance in the presence of reverberation has not been evaluated. By implementing ADMIRE before MV, the benefits of both these beamformers can be achieved. In this article, the assumptions of MV are discussed, specifically their relationship to reverberation clutter. The use of ADMIRE as a preprocessing step to suppress noise from simulations with linear scanning and in vivo curvilinear kidney data is demonstrated, and both narrowband and broadband implementations of MV are applied. With optimal parameters, ADMIRE + MV demonstrated sizing improvements over MV alone by an average of 52.1% in 0-dB signal-to-clutter ratio reverberation cyst simulations and 14.5% in vivo while improving the contrast ratio compared to ADMIRE alone by an average of 15.1% in simulations and 14.0% in vivo. ADMIRE + MV demonstrated a consistent improvement compared to DAS, MV, and ADMIRE both in terms of sizing and contrast ratio.

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.