Lag-Based Filtered-Delay Multiply and Sum Beamformer Combined with Two Phase-Related Factors for Medical Ultrasound Imaging.

A novel adaptive beamformer named filtered-delay multiply and sum (F-DMAS) has recently been proposed. Compared to the delay and sum (DAS) beamforming algorithm, F-DMAS can efficiently improve the resolution and contrast. However, the DAS can still be seen in the expansion of DMAS. Therefore, we rearrange the pair-wised signals in terms of lag in DMAS and then synthesize a lot of new signals. Thanks to the relationship between the spatial coherence and lag, these new signals can be thought of as sorted by the spatial coherence. Thus, we apply two phase-related factors, the polarity-based factor (PF) and the sign coherence factor (SCF), which are evaluated based on new signals, to weight the output of DMAS. The two approaches are consequently referred to as LAG-DMAS-PF and LAG-DMAS-SCF, respectively. The results show that, compared to F-DMAS and DAS, our proposed methods can improve the resolution and contrast to some extent without increasing too much computational complexity. In the comparison between LAG-DMAS-PF and LAG-DMAS-SCF, the latter has better performance, but the former can better protect image details.

Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging.

Beamformer is one of the most important components in ultrasound imaging system. The delay and sum (DAS) beamforming algorithm has been widely used in recent decades due to its simplicity and robustness. However, it has poor impact on resolution and contrast. A new beamformer named filtered delay multiply and sum (F-DMAS) which was an alternative of delay multiply and sum (DMAS) was proposed to overcome these shortcomings of DAS. Although F-DMAS partially enhances the image quality, its performance still has room for improvement. Therefore, a novel beamformer named lag-based delay multiply and sum (L-DMAS) which combines autocorrelation signals with DMAS algorithm is proposed by us to improve its efficiency. Field II was employed to synthesize a point target phantom and a cyst phantom to compare the performance between DAS, F-DMAS, double stage delay multiply and sum (DS-DMAS), and L-DMAS. We also estimate the performance of four algorithms on experimental data and in vivo data. These results show that both DS-DMAS and L-DMAS are better than DAS and F-DMAS in each case. In some cases, DS-DMAS and L-DMAS have little difference in performance, but in other cases, L-DMAS outperforms DS-DMAS. Graphical Abstract.

Artifacts detection-based adaptive filtering to noise reduction of strain imaging.

Strain imaging in medical ultrasound is the imaging modality of elastic properties of biological tissue. In general, strain image will suffer from artifacts noise, which degrades lesion detectability and increases the likelihood of misdiagnosis. How to both suppress artifacts effectively and preserve the structure is vital for diagnosis and also for image post-processing. The bilateral filtering can reduce artifact noise and, at the same time, maintain the tissue structure. However, the balance between noise suppression and edge preservation often makes the threshold selection difficult. This paper is to solve the problem of difficult threshold selection in bilateral filtering. The probability distribution function of amplitude modulation noise in this paper is derived from the statistics of uncompressed speckle. The statistical model of artifact formation is useful for designing an adaptive fast bilateral filter for artifact reduction in ultrasound strain imaging. Both simulation and phantom testing show that the proposed method can improve the quality of ultrasonic strain imaging. Furthermore, the elastographic signal-to-noise ratio was increased by 129.91% and 52.36% for simulated and phantom strain images. The elastographic contrast-to-noise ratio was increased by 521.42% and 218.07% for simulated and phantom strain images, respectively. As indicated by the profiles, the proposed method produces a better result for the purpose of visualization.

A fast bilateral filter with application to artefact reduction.

Elastography in medical ultrasound is an imaging technique that displays information about tissue stiffness. However, elastography suffers from artefact noise that may come from two dominant sources: decorrelation error and amplitude modulation error. In order to reduce artefact and improve the quality of ultrasonic elastography, a fast bilateral filter is proposed in this study based on local histogram. The presented filter is derived from a conventional bilateral filter, and a local histogram is introduced to speed up the filter. The proposed algorithm can reduce artefact noise and, at the same time, maintain the tissue structure. Both simulation and phantom testing show that the proposed method can improve the quality of ultrasonic elastography in terms of tissue elastographic signal-to-noise ratio and elastographic contrast-to-noise ratio values.

Adaptive clutter filter in 2-D color flow imaging based on in vivo I/Q signal.

Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image.

Filter based receive-side spatial compounding for veterinary ultrasound B-mode imaging.

Veterinary ultrasound has been used in a large number of animal husbandry-related circumstances while many corresponding applications also call for the use of ultrasound in human patients. However, veterinary ultrasound images are affected by speckle, an interference pattern that can reduce the quality and contrast of ultrasound images. In this paper, a filter-based receive-side spatial compounding technique for veterinary ultrasound B-Mode imaging is used to create a compounded veterinary B-Mode image based on multiple looks. In particular, filtering in the lateral direction has been proved to be able to preserve the axial information in the sub-bands and to create decorrelation between sub-bands at the expense of some lateral resolution. A new method was proposed to obtain B-Mode IQ data by special veterinary ultrasonic probe. This approach is tested on 275 in-vivo swine. The effect is accomplished in real-time veterinary ultrasonic imaging with a measurable improvement of SNRe. Meanwhile, the speckle and electronic noise in the compounded image have been greatly reduced and smoothed in the visual result.

Corrections to the displacement estimation based on analytic minimization of adaptive regularized cost functions for ultrasound elastography.

Ultrasound elastography has been widely applied in clinical diagnosis. To produce high-quality elastograms, displacement estimation is important to generate ne displacement map from the original ratio-frequency signals. Traditional displacement estimation methods are based on the local information of signals pair, such as cross-correlation method, phase zero estimation. However, the tissue movement is nonlocal during realistic elasticity process due to the compression coming from the surface. Recently, regularized cost functions have been broadly used in ultrasound elastography. In this paper, we tested the using of analytic minimization of adaptive regularized cost function, a combination of different regularized cost functions, to correct the displacement estimation calculated by cross-correlation method directly or by lateral displacement guidance. We have demonstrated that the proposed method exhibit obvious advantages in terms of imaging quality with higher levels of elastographic signal-to-noise ratio and elastographic contrast-to-noise ratio in the simulation and phantom experiments respectively.

Noise reduction for ultrasonic elastography using transmit-side frequency compounding: a preliminary study.

Ultrasonic elastography is an imaging technique providing information about the relative stiffness of biological tissues. In general, elastography suffers from noise artifacts, which degrade lesion detectability and increase the likelihood of misdiagnosis. This paper proposes a method called transmit- side frequency compounding for elastography (TSFC). Beamforming is modified to transmit frames with N alternating center frequencies. Pairs of frames with the same center frequency are used to calculate sub-elastograms that are then averaged to produce one compounded elastogram. Simulation results based on an uniformly elastic tissue model demonstrate the decorrelation among sub-elastograms and the improvement in elastographic signal-to-noise ratio (SNRe) achieved by compounding sub-elastograms. An elastic phantom experiment further validates the noise reduction obtained by the proposed technique.

A real-time display method for ultrasound color flow velocity estimation.

This paper proposes a new way for ultrasound color flow velocity estimation and display. This method sets up a mapping table which directly relates to the dynamic range of the velocity display by using an inverse mapping instead of calculating the arctangent value directly. This method is ideal for software implementation and offers an interactive way to user for changing the dynamic range of flow velocity to increase the display resolution.

A Method for Characteristic Extraction of Ultrasound Doppler Signal with Peak-valley Relationship under Heavy Noise.

This paper proposes a real-time algorithm estimating clinical useful parameters from the maximum frequency curve of ultrasound Doppler spectrum. Traditional methods always apply some pre-calculations to the frequency waveform, for instance, filtering or scaling transformation, which have limitations on real-time features detection and waveform display. In this paper, we propose and maintain a process unit as a section of the waveform with the help of its phase information and the idea of the changeable scaling in the wavelet, to determine the Doppler waveform parameters in real time. From a set of in vivo Doppler waveforms, our proposed algorithm can pick up right parameters even in very noisy environment.