Generalized sidelobe canceler beamforming combined with eigenspace-wiener postfilter for medical ultrasound imaging

Multi-apodization with cross-correlation combined with generalized sidelobe canceller applied to ultrasound imaging

BACKGROUND

Beamforming is vital for medical ultrasound imaging systems. The generalized sidelobe canceller (GSC) beamforming can improve the image quality of lateral resolution, but its performance improvement in contrast and robustness is limited.

OBJECTIVE

This paper proposes an improved generalized sidelobe canceller algorithm based on multi-apodization with cross-correlation (MAXB-IGSC), which aims to improve the contrast and robustness of ultrasound imaging while maintaining the high image resolution and background speckle quality of GSC.

METHODS

The proposed MAXB-IGSC uses multiple pairs of complementary received apodization functions to process the echo data individually to obtain multiple pairs of data sets. The average of their normalized cross-correlation coefficients is then calculated and utilized to determine the adaptive subarray length of the GSC covariance matrix and weights the output of the improved GSC.

RESULTS

The MAXB-IGSC improves the contrast ratio (CR) by 171.18% in anechoic cyst simulation and by 91.23%/130.97%/171.76% in geabr_0 (a dataset from the University of Michigan) experiment compared with GSC, respectively. Furthermore, MAXB-IGSC exhibits significant noise immunity, which greatly improves the robustness of the imaging. The technology also maintains the brightness and uniformity of the background speckle.

CONCLUSION

The proposed MAXB-IGSC has potential for obtaining high-quality ultrasound images in clinical applications.

Tissue ultrasound imaging based on wavelet correlation analysis and pulse-inversion technique

BACKGROUND

Pulse-inversion-based tissue harmonic imaging has been utilized for many years because it can effectively eliminate the harmonic leakage and produce low side-lobe. However, the pulse inversion method is sensitive to imaging object movements, which may result in motion artifacts. Spatial resolution and contrast were limited.

OBJECTIVE

To improve ultrasound image quality by a new pulse-inversion-based tissue harmonic imaging technique.

METHODS

Continuous wavelet transform is applied to investigate the correlation between mother wavelet and the received echoes from two opposite pulses. To get a better correlation, a novel mother wavelet named 'tissue wavelet' is designed based on the Khokhlov-Zabolotskaya- Kuznetsov (KZK) wave equation. Radio frequency data were obtained from open Ultrasonix SonixTouch imaging system. Experiments were carried on ultrasonic tissue phantom, human carotid artery and human liver.

RESULTS

The average improvement of lateral spatial resolution is 49.52% compared to pulse-inversion-based tissue second-harmonic Imaging (PIHI). Contrast ratio (CR) and contrast-to-noise ratio (CNR) increased by 5.55 dB and 1.40 dB over PIHI. Tissue wavelet performs better than Mexh and Morl wavelet in lateral spatial resolution, CR, and CNR.

CONCLUSION

The proposed technique effectively improves the imaging quality in lateral spatial resolution, CR, and CNR.

Improving axial resolution based on the deconvolution recovery method combined with adaptive weighting techniques for ultrasound imaging

BACKGROUND

A fundamental challenge in medical ultrasound imaging is to improve the resolution accurately. Adaptive beamforming is often used to improve lateral resolution, such as minimum variance (MV) and phase coherence factor (PCF). However, it is difficult to improve the axial resolution due to the limitation of the spatial pulse length (SPL) of the transmitted signal.

OBJECTIVE

A deconvolution recovery method combines two adaptive weighting techniques to improve axial resolution.

METHODS

A deconvolution recovery (DR) technique is used to improve axial resolution with a shorter SPL. Then, the DR is combined with MV and PCF (DR-MVPCF) to suppress the sidelobe. The influence of different transmission modes, regularization parameters, and the estimation of point spread function are discussed on the proposed algorithm.

RESULTS

In simulation, DR-MVPCF improved axial resolution from 0.41 mm (0.98 λ) to 0.09 mm (0.21 λ) compared with MV-PCF. In the water bath experiment, DR-MVPCF provided improvement of axial resolution from 0.39 mm (0.93 λ) to 0.07 mm (0.17 λ) compared with MV-PCF. In-vivo data experiment, the DR-MVPCF method increased the speckle signal-to-noise ratio and visibility of the structure while the contrast ratio and contrast-noise ratio decreased.

CONCLUSIONS

The proposed method can improve the axial resolution significantly.

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.