Bubble Wavelet Research Articles

Cumulation, crash, coherency: A cryptocurrency bubble wavelet analysis

After its price peaked in 2017, Bitcoin lost almost half of its value in US Dollars within one month, which in turn is likely to have influenced the behaviour of market participants – many of who were lay investors. We hypothesize that after the peak, there was a structural change in the relationships between cryptocurrencies towards instability, as indicated by increased interdependence. We utilize wavelet coherence analysis of intraday data (5-minute resolution) to investigate the dynamics between a variety of cryptocurrencies in time-frequency space. Accompanied by visualizations depicting bubble dynamics, our robust and highly-significant quantitative results confirm our hypothesis.

Contrast-Enhanced Ultrasound Imaging Based on Bubble Region Detection

The study of ultrasound contrast agent imaging (USCAI) based on plane waves has recently attracted increasing attention. A series of USCAI techniques have been developed to improve the imaging quality. Most of the existing methods enhance the contrast-to-tissue ratio (CTR) using the time-frequency spectrum differences between the tissue and ultrasound contrast agent (UCA) region. In this paper, a new USCAI method based on bubble region detection was proposed, in which the frequency difference as well as the dissimilarity of tissue and UCA in the spatial domain was taken into account. A bubble wavelet based on the Doinikov model was firstly constructed. Bubble wavelet transformation (BWT) was then applied to strengthen the UCA region and weaken the tissue region. The bubble region was thereafter detected by using the combination of eigenvalue and eigenspace-based coherence factor (ESBCF). The phantom and rabbit in vivo experiment results suggested that our method was capable of suppressing the background interference and strengthening the information of UCA. For the phantom experiment, the imaging CTR was improved by 10.1 dB compared with plane wave imaging based on delay-and-sum (DAS) and by 4.2 dB over imaging based on BWT on average. Furthermore, for the rabbit kidney experiment, the corresponding improvements were 18.0 dB and 3.4 dB, respectively.

Wavelet-transform-based active imaging of cavitation bubbles in tissues induced by high intensity focused ultrasound.

Cavitation detection and imaging are essential for monitoring high-intensity focused ultrasound (HIFU) therapies. In this paper, an active cavitation imaging method based on wavelet transform is proposed to enhance the contrast between the cavitation bubbles and surrounding tissues. The Yang-Church model, which is a combination of the Keller-Miksis equation with the Kelvin-Voigt equation for the pulsations of gas bubbles in simple linear viscoelastic solids, is utilized to construct the bubble wavelet. Experiments with porcine muscles demonstrate that image quality is associated with the initial radius of the bubble wavelet and the scale. Moreover, the Yang-Church model achieves a somewhat better performance compared with the Rayleigh-Plesset-Noltingk-Neppiras-Poritsky model. Furthermore, the pulse inversion (PI) technique is combined with bubble wavelet transform to achieve further improvement. The cavitation-to-tissue ratio (CTR) of the best tissue bubble wavelet transform (TBWT) mode image is improved by 5.1 dB compared with that of the B-mode image, while the CTR of the best PI-based TBWT mode image is improved by 7.9 dB compared with that of the PI-based B-mode image. This work will be useful for better monitoring of cavitation in HIFU-induced therapies.

High-contrast active cavitation imaging technique based on multiple bubble wavelet transform.

In this study, a unique method that combines the ultrafast active cavitation imaging technique with multiple bubble wavelet transform (MBWT) for improving cavitation detection contrast was presented. The bubble wavelet was constructed by the modified Keller-Miksis equation that considered the mutual effect among bubbles. A three-dimensional spatial model was applied to simulate the spatial distribution of multiple bubbles. The effects of four parameters on the signal-to-noise ratio (SNR) of cavitation images were evaluated, including the following: initial radii of bubbles, scale factor in the wavelet transform, number of bubbles, and the minimum inter-bubble distance. And the other two spatial models and cavitation bubble size distributions were introduced in the MBWT method. The results suggested that in the free-field experiments, the averaged SNR of images acquired by the MBWT method was improved by 7.16 ± 0.09 dB and 3.14 ± 0.14 dB compared with the values of images acquired by the B-mode and single bubble wavelet transform (SBWT) methods. In addition, in the tissue experiments, the averaged cavitation-to-tissue ratio of cavitation images acquired by the MBWT method was improved by 4.69 ± 0.25 dB and 1.74± 0.29 dB compared with that of images acquired by B-mode and SBWT methods.

Ultrasound Contrast Plane Wave Imaging Based on Bubble Wavelet Transform: In Vitro and In Vivo Validations

The aim of the study described here was to develop an ultrasound contrast plane wave imaging (PWI) method based on pulse-inversion bubble wavelet transform imaging (PIWI) to improve the contrast-to-tissue ratio of contrast images. A pair of inverted “bubble wavelets” with plane waves was constructed according to the modified Herring equation. The original echoes were replaced by the maximum wavelet correlation coefficients obtained from bubble wavelet correlation analysis. The echoes were then summed to distinguish microbubbles from tissues. In in vivo experiments on rabbit kidney, PIWI improved the contrast-to-tissue ratio of contrast images up to 4.5 ± 1.5 dB, compared with that obtained in B-mode (p < 0.05), through use of a pair of inverted plane waves. The disruption rate and infusion time of microbubbles in PIWI-based PWI were then quantified using two perfusion parameters, area under the curve and half transmit time estimated from time–intensity curves, respectively. After time–intensity curves were denoised by detrended fluctuation analysis, the average area under the curve and half transit time of PIWI-based PWI were 55.94% (p < 0.05) and 20.51% (p < 0.05) higher than those of conventional focused imaging, respectively. Because of its high contrast-to-tissue ratio and low disruption of microbubbles, PIWI-based PWI has a long infusion time and is therefore beneficial for transient monitoring and perfusion assessment of microbubbles circulating in vessels.

Acoustic methods for cavitation mapping in biomedical applications

In recent years, cavitation is increasingly utilized in a wide range of applications in biomedical field. Monitoring the spatial-temporal evolution of cavitation bubbles is of great significance for efficiency and safety in biomedical applications. In this paper, several acoustic methods for cavitation mapping proposed or modified on the basis of existing work will be presented. The proposed novel ultrasound line-by-line/plane-by-plane method can depict cavitation bubbles distribution with high spatial and temporal resolution and may be developed as a potential standard 2D/3D cavitation field mapping method. The modified ultrafast active cavitation mapping based upon plane wave transmission and reception as well as bubble wavelet and pulse inversion technique can apparently enhance the cavitation to tissue ratio in tissue and further assist in monitoring the cavitation mediated therapy with good spatial and temporal resolution. The methods presented in this paper will be a foundation to promote the research and development of cavitation imaging in non-transparent medium.

Ultrafast active cavitation imaging with enhanced cavitation to tissue ratio based on wavelet transform and pulse inversion.

The quality of ultrafast active cavitation imaging (UACI) using plane wave transmission is hindered by low transmission pressure, which is necessary to prevent bubble destruction. In this study, a UACI method that combined wavelet transform with pulse inversion (PI) was proposed to enhance the contrast between the cavitation bubbles and surrounding tissues. The main challenge in using wavelet transform is the selection of the optimum mother wavelet. A mother wavelet named "cavitation bubble wavelet" and constructed according to Rayleigh-Plesset-Noltingk-Neppiras-Poritsky model was expected to obtain a high correlation between the bubbles and beamformed echoes. The method was validated by in vitro experiments. Results showed that the image quality was associated with the initial radius of bubble and the scale. The signal-to-noise ratio (SNR) of the best optimum cavitation bubble wavelet transform (CBWT) mode image was improved by 3.2 dB compared with that of the B-mode image in free-field experiments. The cavitation-to-tissue ratio of the best optimum PI-based CBWT mode image was improved by 2.3 dB compared with that of the PI-based B-mode image in tissue experiments. Furthermore, the SNR versus initial radius curve had the potential to estimate the size distribution of cavitation bubbles.

A Lifting Wavelet Structure Based on Lateral Inhibition Characteristics

Aiming at the question of infrared image edge to enhance and the real-time processing, this paper researches a Bubble wavelet construction process which can remove redundant information, strengthen the difference of information and have the lateral inhibition characteristics ,derives the Bubble wavelet lifting scheme and the lifting coefficient , and finally with the application of the lifting scheme, we realize the parallel computing aiming at the infrared image decomposition and reconstruction, the results show that based on lateral inhibition characteristics of the Bubble wavelet lifting scheme is correct, and also proves the usability of the lifting coefficient.

Ultrasound Contrast Imaging Based on a Novel Algorithm Combined Pulse Inversion with Wavelet Transform

In this article, an ultrasound contrast imaging method that combines the pulse-inversion technique with wavelet transform has been proposed to enhance the contrast between bubbles and surrounding tissues. In this technique, wavelet transform is utilized to analyze the correlation between mother wavelet and the received echoes from a pair of inverted transmit pulses, respectively. To obtain a better correlation, a new mother wavelet named “bubble wavelet” is constructed according to the modified Herring equation. Radio-frequency (RF) data were acquired from a modified digital diagnostic ultrasound system that transmits two identical pulses with opposite polarity. The proposed method was validated by simulations. Experiments were performed on an ultrasound flow phantom and results showed that the contrast-to-tissue ratio (CTR) was improved by up to 28 dB depending on types of mother wavelet, scales and depths, compared with that obtained using pulse-inversion-based second-harmonic imaging. Experiments in vivo were also conducted out using kidneys of rabbits and results showed that the signals of surrounding tissues can be well suppressed compared with that of bubbles. The proposed method was compared with the quadratic pulse inversion (QPI) imaging on the same set of experimental data. Further improvements might be achieved with optimized bubble wavelet and imaging algorithm.