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Microwave imaging is a highly promising modality for the early detection of breast cancer. A multitude of image reconstruction algorithms have been devised. Previous methods utilized the coherence factor (CF) to enhance image quality. However, CF‐based methods often oversuppress the desired signals and introduce image artifacts when the signal‐to‐noise ratio is low. This study introduces a scaled coherence factor‐based delay multiply and sum (DMAS) Beamforming technique to achieve good noise suppression while maintaining robustness. The performance of this method was evaluated using datasets derived from an experimental breast phantom. The results show that the proposed method achieves improvements of signal‐to‐clutter ratio by 26%, signal‐to‐mean ratio by 7%, full‐width at half‐maximum by 8%, and localization error by 51% compared to the CF‐DMAS method. The suggested microwave imaging approach for breast cancer detection provides high resolution, contrast, and localization accuracy along with low computational complexity. [ABSTRACT FROM AUTHOR]

Breast cancer is a global health concern, emphasizing the need for early detection. However, current mammography struggles to effectively image dense breasts. Breast ultrasound can be an adjunctive method, but it is highly dependent on operator skill. Ultrasound computed tomography (USCT) reflection imaging provides high-quality 3D images, but often uses delay-and-sum (DAS) beamforming, which limits its image quality. This article proposes the integration of coherence-factor (CF) beamforming into ultrasound computed tomography (USCT) reflection imaging to enhance image quality. CF assesses the focus quality of beamforming by analyzing the signal coherence across different channels, assigning higher weights to high-quality focus points and thereby improving overall image quality. Numerical simulations and phantom experiments using our built USCT prototype were conducted to optimize the imaging parameters and assess and compare the image quality of CF and DAS beamforming. Numerical simulations demonstrated that CF beamforming can significantly enhance image quality. Phantom experiments with our prototype revealed that CF beamforming significantly improves image resolution (from 0.35 mm to 0.14 mm) and increases contrast ratio (from 24.54 dB to 63.28 dB). The integration of CF beamforming into USCT reflection imaging represents a substantial improvement in image quality, offering promise for enhanced breast cancer detection and imaging capabilities. [ABSTRACT FROM AUTHOR]

We introduce a highly efficient 48-channel ultrasound beamforming system ideal for ultrasound endoscopy applications. The system includes a transmitter and a receiver that allows for low-area, high-resolution imaging acquisition. The transmitter uses a charge redistribution HV (high-voltage) scheme to generate three-level pulses that actuate the transducer, implemented with the standard CMOS process for optimal cost and power savings. Meanwhile, the receiver features a sub-array structure and a delay generator that reduces the area usage. To achieve high-resolution ultrasound imaging acquisition with low computational power, we developed a Shift Coherence Factor (SCF) algorithm that is hardware-friendly. This approach delivers a lateral resolution of over 20% better than that of the conventional delay and sum (DAS) algorithm, with a contrast ratio of over 30 dB. The system was implemented in a 180 nm standard CMOS process with an area of 24.98 mm2, power consumption of 8.23 mW per channel, achieving a delay resolution of 8.33 ns, and a low-area implementation of 0.52 mm2 per channel. The system offers high-quality imaging acquisition with minimal additional area and power consumption, which has great potential for 3D imaging or catheterized ultrasound systems. [ABSTRACT FROM AUTHOR]

Purpose: In the receive beamforming of an ultrasonography system, a B-mode image is reconstructed by assuming an average speed of sound (SoS) as a constant value. In our previous studies, we proposed a method for estimating the average SoS based on the coherence factor (CF) and the reciprocal of phase variances of element signals in delay-and-sum (DAS) beamforming. In this paper, we investigate the accuracy of estimation of the average SoS for compound imaging. Methods: For this purpose, two numerical simulations were performed with k-Wave software. Also, the estimation methods based on the CF and the reciprocal were applied to in vivo data from the common carotid artery, and B-mode images were reconstructed using the estimated average SoS. Results: In the first numerical simulation using an inhomogeneous phantom, the relationship between the accuracy and the transmission angles for the estimation was investigated, and the root mean squared errors (RMSEs) of estimates obtained based on the CF and the reciprocal of the phase variance were 1.25 ± 0.09, and 0.765 ± 0.17% at the transmission sequence of steering angles of (− 10°, − 5°, 0°, 5°, 10°), respectively. In the second numerical simulation using a cyst phantom, lateral resolutions were improved by reconstructing the image using the estimates obtained using the proposed strategy (reciprocal). By the proposed strategy, improvement of the continuity of the lumen–intima interface in the lateral direction was observed in the in vivo experiment. Conclusion: Consequently, the results indicated that the proposed strategy was beneficial for estimation of the average SoS and image reconstruction. [ABSTRACT FROM AUTHOR]

Delay multiply and sum beamforming (DMAS) is a non-linear method used in ultrasound imaging which offers superior performance to conventional delay and sum beamforming (DAS). While the combination of DMAS and coherence factor (CF) can further improve single plane-wave imaging lateral resolution, by using CF to weight the DMAS output, the main lobe width and aberration effects can be suppressed, which will improve the disadvantage of low lateral resolution when imaging with a single plane-wave. However, in low signal-to-noise ratio (SNR) environments, the speckle variance of the image increases, and there are black area artifacts around high echo objects. To improve the quality of the scatter without significantly reducing the lateral resolution of the DMAS-CF, this paper proposes an adaptive spatio-temporally smoothed coherence factor (GSTS-CF) combined with delay multiply and sum beamformer (DMAS + GSTS-CF), which uses the generalized coherence factor (GCF) as a local coherence detection tool to adaptively determine the subarray length to obtain an improved adaptive spatio-temporally smoothed factor, and uses this factor to weight the output of DMAS. The simulation and experimental data show that the proposed method improves lateral resolution (20 mm depth) by 86.87% compared to DAS, 52.13% compared to DMAS, 15.84% compared to DMAS + STS-CF, and has a full width at half maxima (FWHM) similar to DMAS-CF. The proposed method improves the speckle signal-to-noise ratio (sSNR) by 87.85% (simulation) and 77.84% (in carotid) compared to DMAS-CF, 20.37% (simulation) and 40.74% (in carotid) compared to DMAS, 15.03% (simulation) and 13.46% (in carotid) compared to DMAS + STS-CF, and has sSNR and scatter variance similar to DAS. This indicates that the method improves scatter quality (lower scatter variance and higher sSNR) without significantly reducing lateral resolution. [ABSTRACT FROM AUTHOR]

Multiple-input-multiple-output synthetic aperture radar (MIMO-SAR) is being studied and applied in more and more scenarios. However, there is still a certain distance away from real-time imaging using advanced algorithms. The traditional backpropagation algorithm (BPA) multi-accumulation integration is unsuitable for dealing with large-size scanning data, and the wavenumber domain algorithm requires the array to satisfy Nyquist sampling law in azimuth to avoid aliasing in imaging reconstruction. Based on these issues, a novel 3D imaging method is proposed for MIMO-SAR. An appropriate transformation and inverse Fourier transform (FT) is carried out for the frequency domain; thus, accumulation in the wavenumber domain is not required, which is easy to implement. The computational complexity of the algorithm is much lower than BPA and has better generalizability than the wavenumber domain algorithm. Coherence factor (CF) is also introduced to achieve sidelobe suppression. Proof-of-principle experiments were also carried out in the 92.5 GHz band based on the MIMO-SAR prototype system. Both simulation and experimental results of different distributed targets show good performance of imaging and do not lose the quality of image reconstruction. [ABSTRACT FROM AUTHOR]

This is the first article in a series of two dealing with a matrix approach for aberration quantification and correction in ultrasound imaging. Advanced synthetic beamforming relies on a double focusing operation at transmission and reception on each point of the medium. Ultrasound matrix imaging (UMI) consists in decoupling the location of these transmitted and received focal spots. The response between those virtual transducers form the so-called focused reflection matrix that actually contains much more information than a confocal ultrasound image. In this paper, a time-frequency analysis of this matrix is performed, which highlights the single and multiple scattering contributions as well as the impact of aberrations in the monochromatic and broadband regimes. Interestingly, this analysis enables the measurement of the incoherent input-output point spread function at any pixel of this image. A fitting process enables the quantification of the single scattering, multiple scattering and noise components in the image. From the single scattering contribution, a focusing criterion is defined, and its evolution used to quantify the amount of aberration throughout the ultrasound image. In contrast to the state-of-the-art coherence factor, this new indicator is robust to multiple scattering and electronic noise, thereby providing a contrasted map of the focusing quality at a much better transverse resolution. After a validation of the proof-of-concept based on time-domain simulations, UMI is applied to the in-vivo study of a human calf. Beyond this specific example, UMI opens a new route for speed-of-sound and scattering quantification in ultrasound imaging. [ABSTRACT FROM AUTHOR]

The steered response power (SRP) method has been widely used in acoustic source localization because of its high accuracy and strong anti-noise ability. However, it has many local extrema, which affects the reliability of localization and results in high computational cost. In this paper, the spatial response of the SRP is defined to explain the SRP. Based on this, the formation mechanism of local extrema is analyzed, that is, the local extrema are related to the coherence of the generalized cross-correlation involved in the accumulation. The coherence can be evaluated by a coherence factor constructed from a statistical point of view. The SRP with coherence constraint is proposed, which is a simple and very effective method to suppress local extrema. Compared with the traditional SRP, the localization results of the simulation and actual data show that the proposed method can effectively suppress the local extrema without the loss of the localization accuracy of the traditional SRP method. [ABSTRACT FROM AUTHOR]

Aiming at the high correlation characteristics of ultrasound echo signals, a delay multiplication and sum beamforming algorithm based on improved coherence factor (pCF-DMAS) is proposed and applied to plane wave ultrasound imaging. The algorithm calculates the weight of the echo signal by enhancing the coherence of the coherence factor, and then performs multiplication and sum operations. By using Field II to perform simulation experiments on ultrasound point targets and cyst targets, the imaging results are analyzed to verify the effectiveness of the algorithm. The simulation results show that the algorithm has excellent laterally resolution, and has the highest contrast when p is 0.7. With the imaging effects of point targets and cyst targets considered, the optimal p value of the algorithm is proposed to be 0.3. Compared with the delay stacking and delay multiplication and sum beamforming algorithms, the CR of the image is increased by 12.559, 9.602dB, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a two-dimensional mean adaptive zero-crossing factor (TMAZF) is proposed to enhance the contrast ratio and resolution of the images generated by coherent plane-wave compounding (CPWC). TMAZF determines the zero-crossing point based on the polarity of the plane wave imaging results and adaptively adjusts the length of the subarrays, then calculates the average values using the two-dimensional mean filter. It can restrain noise and maintain the background speckle pattern. The performance of the proposed method is verified by simulations and experiments. The datasets processing results show that this method can effectively improve the contrast ratio and resolution than traditional CPWC. To analyze the quality of imaging results quantitatively, TMAZF is compared with traditional CPWC, coherence factor weighted CPWC and generalized coherence factor weighted CPWC in this paper. For simulated cyst images and carotid artery images in vivo, the contrast ratio of TMAZF has been greatly improved. Besides, in the experimental data, the contrast-to-noise ratio and speckle signal-to-noise ratio of TMAZF also have obvious advantages over those of other methods and show good potential in practical application. [ABSTRACT FROM AUTHOR]

Abstract Background The eigenspace generalized sidelobe canceller (EGSC) beamformer combined with a signal-to-noise ratio (SNR) dependent coherence factor (CF) is suggested for coherent plane wave compounding (PW) imaging. Conventional CF based methods such as generalized CF and subarray CF can improve the image quality, however, they are not suitable for low SNR. On the other hand, the EGSC CF based approach can introduce improvements in image quality, however, in PW imaging is susceptible to suffer from degradation due to low SNR which leads to a poor image quality. To overcome this limitation, the SNR dependent CF method is suggested for application in such situations due to its ability to control the SNR levels. Methods The Field II and the Verasonics ultrasound imaging system with a L11-4v array transducer with a contrast resolution phantom were used to capture the plane wave sequences of simulation and experimental data, respectively. The performance evaluation using full width at half maximum (FWHM), contrast (CR and CNR) and the speckle statistics by using the signal to noise ratio (SNR) complemented by the Rayleigh distribution analysis was performed. In order to evaluate the performance of the $$\text {EGSC}_{3}$$ EGSC3 (the SNR CF) beamformer, the comparison is done with particular importance to other CF-based approaches such as $$\text {EGSC}_{1}$$ EGSC1 (the generalized CF) and, $$\text {EGSC}_{2}$$ EGSC2 (the subarray CF) respectively. Results Taking DAS as reference, $$\text {EGSC}_3$$ EGSC3 showed 30.3 and 39.5% of improvement for $$\text {CR(dB)}$$ CR(dB) and $$\text {CNR}$$ CNR , respectively, when using experimental data. The proposed method also slightly outperforms the $$\text {EGSC}_1$$ EGSC1 and $$\text {EGSC}_2$$ EGSC2 methods for $$\text {CR(dB)}$$ CR(dB) , $$\text {CNR}$$ CNR , and speckle statistics assessment. Conclusion The $$\text {EGSC}_3$$ EGSC3 is, therefore, suitable for CPWC by improving the spatial resolution and contrast while preserving the speckle pattern.

This paper addresses the analysis of textured images using the symmetric positive semi-definite matrix. In particular, a field of symmetric positive semi-definite matrices is used to estimate the structural information represented by the local orientation and the degree of anisotropy in structured and sinusoid-like textured images. In order to ensure faithful local structure estimation, an adaptive algorithm for the regularization of the extent of gradient fields smoothing is proposed. Results obtained on different texture samples show the strength of the proposed method in accurately representing the local variation of orientations in the underlying textured images, which paves the way towards an accurate analysis of the texture structures.

Coherent plane-wave compounding (CPWC) is widely used in medical ultrasound imaging, in which plane-waves tilted at multiple angles are used to reconstruct ultrasound images. CPWC helps to achieve a balance between frame rate and image quality. However, the image quality of CPWC is limited due to sidelobes and noise interferences. Filtering techniques and adaptive beamforming methods are commonly used to suppress noise and sidelobes. Here, we propose a neighborhood singular value decomposition (NSVD) filter to obtain high-quality images in CPWC. The NSVD filter is applied to adaptive beamforming by combining with adaptive weighting factors. The NSVD filter is advantageous because of its singular value decomposition (SVD) and smoothing filters, performing the SVD processing in neighboring regions while using a sliding rectangular window to filter the entire imaging region. We also tested the application of NSVD in adaptive beamforming. The NSVD filter was combined with short-lag spatial coherence (SLSC), coherence factor (CF), and generalized coherence factor (GCF) to enhance performances of adaptive beamforming methods. The proposed methods were evaluated using simulated and experimental datasets. We found that NSVD can suppress noise and achieve improved contrast (contrast ratio (CR), contrast-to-noise ratio (CNR) and generalized CNR (gCNR)) compared to CPWC. When the NSVD filter is used, adaptive weighting methods provide higher CR, CNR, gCNR and speckle signal-to-noise ratio (sSNR), indicating that NSVD is able to improve the imaging performance of adaptive beamforming in noise suppression and speckle pattern preservation. [ABSTRACT FROM AUTHOR]

Handheld ultrasound devices have been widely used for diagnostic applications. The use of the acoustic-field beamforming (AFB) method has been proposed for handheld ultrasound to reduce electricity consumption and avoid battery and unwanted heat issues. However, the image quality, such as the contrast ratio and contrast-to-noise-ratio, are poorer with this technique than with the conventional delay-and-sum method. To address the problems associated with the worse image quality in AFB imaging, in this paper we propose the use of an AFB-based generalized coherence factor (GCF) technique, in which the GCF weighting developed for adaptive beamforming is extended to AFB. Simulation data, experimental results, and in vivo testing verified the efficacy of our proposed AFB-based GCF technique.

Terahertz (THz) arrays can be used to improve the data acquisition speed considerably in realtime imaging applications. However, the THz array imaging usually suffers from the side-lobe artifacts, which leads to a severe decline in the image quality. In this paper, a side-lobe suppression method based on coherence factor is proposed to improve the image quality. The influences of signal-to-noise ratio on the imaging results are analyzed by simulation. Furthermore, the results based on the real-world data validate the effectiveness of the proposed method, which indicates that the side-lobe is suppressed by 29 dB. This paper can benefit the development of THz imaging technique and its applications in real-time imaging realms.

Synthetic transmit aperture (STA) ultrasound imaging that obtain bi-directional focusing can create a high-resolution image. Delay-and-sum (DAS) approach is performed in both transmit and receive modes, which leads to low contrast and high sidelobe. Adaptive weighting technology is effective in improving image quality. This paper proposes a new adaptive weighting factor namely signal eigenvalue factor (SEF) for STA imaging. SEF performs eigenvalue decomposition on transmitting aperture, and then it uses the larger eigenvalues as the weighting factor to carry out the adaptive imaging. For comparison, conventional coherence factor (CF) method is also presented. Simulation and experimental results show that SEF method can get higher resolution than CF and DAS. In addition, the contrast radio and contrast-to-noise radio can be enhanced, especially for massive cyst.

Many adaptive beamformers claim to produce images with increased contrast, a feature that could enable a better detection of lesions and anatomical structures. Contrast is often quantified using the contrast ratio (CR) and the contrast-to-noise ratio (CNR). The estimation of CR and CNR can be affected by dynamic range alterations (DRAs), such as those produced by a trivial gray-level transformation. Thus, we can form the hypothesis that contrast improvements from adaptive beamformers can, partly, be due to DRA. In this paper, we confirm this hypothesis. We show evidence on the influence of DRA on the estimation of CR and CNR and on the fact that several methods in the state of the art do alter the DR. To study this phenomenon, we propose a DR test (DRT) to estimate the degree of DRA and we apply it to seven beamforming methods. We show that CR improvements correlate with DRT with $R^{2}\text {-adj}=0.88$ in simulated data and $R^{2}\text {-adj}=0.98$ in experiments. We also show that DRA may lead to increased CNR values, under some circumstances. These results suggest that claims on lesion detectability, based on CR and CNR values, should be revised. [ABSTRACT FROM AUTHOR]

Purpose: Ultrasound beamforming is required to obtain clinical ultrasound images. In the beamforming procedure, the distance between the receiving focal point and each transducer element is determined based on the assumed speed of sound in the tissue. However, the actual speed of sound in tissue is unknown and varies depending on the tissue type. To improve the performance of an ultrasonic beamformer by evaluating its focusing quality, the coherence factor (CF) was introduced in medical ultrasound imaging. The CF may be used to estimate the speed of sound in tissue because it can identify focusing errors in beamforming. In the present study, the feasibility of CF for estimating the speed of sound was examined through phantom experiments. Method: To evaluate the dependency of CF on the assumed speed of sound in ultrasound beamforming, beamformed ultrasonic radio frequency (RF) signals and CFs were obtained at different assumed speeds of sound. CF is highest when the assumed speed of sound matches the true speed of sound in the medium. Therefore, the speed of sound in the medium was determined as the assumed speed of sound, which gives the highest CF. The proposed method was validated in a conventional line-by-line sequence with a focused transmit beam and ultrafast plane wave imaging. Results: A homogeneous phantom (diffuse scattering medium) with a known speed of sound of 1540 m/s was used for validating the proposed method. Beamformed ultrasonic RF signals and CFs were obtained at an assumed speed of sound from 1480 to 1600 m/s varied at a pitch of 5 m/s. In the line-by-line sequence, CF reached the maximum at an assumed speed of sound of 1525.0 m/s (0.97% difference from the true value) when CFs at all spatial points in the region of interest (ROI) were averaged. On the other hand, the speed of sound was determined to be 1528.5 m/s (0.75% difference) when CFs at spatial points with CF-weighted echo amplitudes were larger than 20% of the maximum value. In plane wave imaging, the speed of sound was estimated to be 1544.5 m/s (0.29% difference) using CFs with CF-weighted echo amplitudes larger than 20% of the maximum value. Conclusion: The speed of sound of a homogeneous medium could be determined by the proposed method with errors of less than 1% using CFs obtained from ultrasonic echo signals selected based on the CF-weighted echo amplitudes, i.e., when echo signals with better signal-to-noise ratios (SNRs) were used. [ABSTRACT FROM AUTHOR]

Coherent plane-wave compounding (CPWC) is widely used in medical ultrasound imaging, in which plane-waves tilted at multiple angles are used to reconstruct ultrasound images. CPWC helps to achieve a balance between frame rate and image quality. However, the image quality of CPWC is limited due to sidelobes and noise interferences. Filtering techniques and adaptive beamforming methods are commonly used to suppress noise and sidelobes. Here, we propose a neighborhood singular value decomposition (NSVD) filter to obtain high-quality images in CPWC. The NSVD filter is applied to adaptive beamforming by combining with adaptive weighting factors. The NSVD filter is advantageous because of its singular value decomposition (SVD) and smoothing filters, performing the SVD processing in neighboring regions while using a sliding rectangular window to filter the entire imaging region. We also tested the application of NSVD in adaptive beamforming. The NSVD filter was combined with short-lag spatial coherence (SLSC), coherence factor (CF), and generalized coherence factor (GCF) to enhance performances of adaptive beamforming methods. The proposed methods were evaluated using simulated and experimental datasets. We found that NSVD can suppress noise and achieve improved contrast (contrast ratio (CR), contrast-to-noise ratio (CNR) and generalized CNR (gCNR)) compared to CPWC. When the NSVD filter is used, adaptive weighting methods provide higher CR, CNR, gCNR and speckle signal-to-noise ratio (sSNR), indicating that NSVD is able to improve the imaging performance of adaptive beamforming in noise suppression and speckle pattern preservation.

We present an enhanced imaging procedure for suppression of the rough surface clutter arising in forward-looking ground-penetrating radar (FL-GPR) applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging, and employs coherence factor (CF) for clutter suppression. After tomographic reconstruction, the CF is first applied to generate a “coherence map” of the region in front of the FL-GPR system illuminated by the transmitting antennas. A pixel-by-pixel multiplication of the tomographic image with the coherence map is then performed to generate the clutter-suppressed image. The effectiveness of the CF approach is demonstrated both qualitatively and quantitatively using electromagnetic modeled data of metallic and plastic shallow-buried targets.

Natural seepage of methane into the oceans is considerable, and plays a role in the global carbon cycle. Estimating the amount of this greenhouse gas entering the water column is important in order to understand their environmental impact. In addition, leakage from man-made structures such as gas pipelines may have environmental and economical consequences and should be promptly detected. Split beam echo sounders (SBES) detect hydroacoustic plumes due to the significant contrast in acoustic impedance between water and free gas. SBES are also powerful tools for plume characterization, with the ability to provide absolute acoustic measurements, estimate bubble trajectories, and capture the frequency dependent response of bubbles. However, under challenging conditions such as deep water and considerable background noise, it can be difficult to detect the presence of gas seepage from the acoustic imagery alone. The spatial coherence of the wavefield measured across the split beam sectors, quantified by the coherence factor (CF), is a computationally simple, easily available quantity which complements the acoustic imagery and may ease the ability to automatically or visually detect bubbles in the water column. We demonstrate the benefits of CF processing using SBES data from the Hudson Canyon, acquired using the Simrad EK80 SBES. We observe that hydroacoustic plumes appear more clearly defined and are easier to detect in the CF imagery than in the acoustic backscatter images. [ABSTRACT FROM AUTHOR]

Ultrafast ultrasound imaging is a promising technique for measurement of fast moving objects. In ultrafast ultrasound imaging, the high temporal resolution is realized at the expense of the lateral spatial resolution and image contrast. The lateral resolution and image contrast are important factors determining the quality of a B-mode image, and methods for improvements of the lateral resolution and contrast have been developed. In the present study, we focused on two signal processing techniques; one is an adaptive beamformer, and the other is the phase coherence factor (PCF). By weighting the output of the modified amplitude and phase estimation (mAPES) beamformer by the phase coherence factor, image quality was expected to be improved. In the present study, we investigated how to implement the PCF into the mAPES beamformer. In one of the two examined strategies, the PCF is estimated using element echo signals before application of the weight vector determined by the adaptive beamformer. In the other strategy, the PCF was evaluated from the element signals subjected to the mAPES beamformer weights. The performance of the proposed method was evaluated by the experiments using an ultrasonic imaging phantom. Using the proposed strategies, the lateral full widths at half maximum (FWHM) were both 0.288 mm, which was better than that of 0.348 mm obtained by the mAPES beamformer only. Also, the image contrasts realized by the mAPES beamformer with the PCFs estimated before and after application of the mAPES beamformer weights to the element signals were 5.61 dB and 5.32 dB, respectively, which were better than that of 5.14 dB obtained by the mAPES beamformer only. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Ultrasound image quality is related to the receive beamformer's ability. Delay and sum (DAS), a conventional beamformer, is combined with the coherence factor (CF) technique to suppress side lobe levels. The purpose of this study is to improve these beamformer's abilities. Methods: It has been shown that extension of the receive aperture can improve the receive beamformer's ability in radar studies. This paper shows that the focusing quality of CF and CF+DAS in medical ultrasound can be increased by extension of the receive aperture's length in phased synthetic aperture (PSA) imaging. Results: The 3-dB width of the main lobe in the receive beam related to CF focusing decreased to 0.55 mm using the proposed PSA compared to the conventional phased array (PHA) imaging, whose FWHM is about 0.9 mm. The clutter-to-total-energy ratio (CTR) represented by R20 dB showed an improvement of 50 and 33% for CF and CF+DAS beamformers, respectively, with PSA as compared to PHA. In addition, simulation results validated the effectiveness of PSA versus PHA. Conclusion: In applications where there are no important limitations on the SNR, PSA imaging is recommended as it increases the ability of the receive beamformer for better focusing. [ABSTRACT FROM AUTHOR]

Tissue harmonic imaging (THI) utilizes harmonic signals generating within the tissue as the result of nonlinear acoustic wave propagation. With inadequate transmitting acoustic energy, THI is incapable to detect the small objects since poor harmonic signals have been generated. In most cases, high transmission energy cannot be guaranteed because of the imaging safety issue or specific imaging modality such as the plane wave imaging (PWI). Discrimination of small point targets such as calcification, however, is particularly important in the ultrasound diagnosis. Few efforts have been made to pursue the THI with high resolution and good small target visibility at the same time. In this paper, we proposed a new eigenspace-based coherence factor (ESBCF) beamformer to solve this problem. A new kind of coherence factor (CF), named as ESBCF, is firstly proposed to detect the point targets. The detected region-of-interest (ROI) is then enhanced adaptively by using a newly developed beamforming method. The ESBCF combines the information from signal eigenspace and coherence factor by expanding the CF to the covariance matrix of signal. Analogous to the image processing but in the radio frequency (RF) data domain, the proposed method fully utilizes the information from the fundamental and harmonic components. The performance of the proposed method is demonstrated by simulation and phantom experiments. The improvement of the point contrast ratio (PCR) is 7.6 dB in the simulated data, and 6.0 dB in the phantom experiment. Thanks to the improved small point detection ability of the ESBCF, the proposed beamforming algorithm can enhance the PCR considerably and maintain the high resolution of the THI at the same time. [ABSTRACT FROM AUTHOR]

Ultrafast ultrasound imaging is a promising technique for measurement of fast moving objects. In ultrafast ultrasound imaging, the high temporal resolution is realized at the expense of the lateral spatial resolution and image contrast. The lateral resolution and image contrast are important factors determining the quality of a B-mode image, and methods for improvements of the lateral resolution and contrast have been developed. In the present study, we focused on two signal processing techniques; one is an adaptive beamformer, and the other is the phase coherence factor (PCF). By weighting the output of the modified amplitude and phase estimation (mAPES) beamformer by the phase coherence factor, image quality was expected to be improved. In the present study, we investigated how to implement the PCF into the mAPES beamformer. In one of the two examined strategies, the PCF is estimated using element echo signals before application of the weight vector determined by the adaptive beamformer. In the other strategy, the PCF was evaluated from the element signals subjected to the mAPES beamformer weights. The performance of the proposed method was evaluated by the experiments using an ultrasonic imaging phantom. Using the proposed strategies, the lateral full widths at half maximum (FWHM) were both 0.288 mm, which was better than that of 0.348 mm obtained by the mAPES beamformer only. Also, the image contrasts realized by the mAPES beamformer with the PCFs estimated before and after application of the mAPES beamformer weights to the element signals were 5.61 dB and 5.32 dB, respectively, which were better than that of 5.14 dB obtained by the mAPES beamformer only.

Purpose: Spatial resolution is one of the important factors that determines ultrasound image quality. In the present study, methods using the phase variance of ultrasonic echoes received by individual transducer elements have been examined for improvement of spatial resolution. Method: An imaging method, i.e., phase coherence imaging, which uses the phase coherence factor (PCF) obtained from the phase variance of received ultrasonic echoes, was recently proposed. Spatial resolution is improved by weighting ultrasonic RF signals obtained by delay-and-sum (DAS) beam forming using PCF. In the present study, alternative PCFs, i.e., exponential PCF, harmonic PCF, and Gaussian PCF, have been proposed and examined for further improvement of spatial resolution. Result: Spatial resolutions realized by the proposed PCFs were evaluated by an experiment using a phantom. The full widths at half maxima of the lateral profiles of an echo from a string phantom were 2.61 mm (DAS only), 1.46 mm (conventional PCF), and 0.48-0.62 mm (proposed PCFs). Conclusion: The PCFs newly proposed in the present study showed better spatial resolutions than the conventional PCF. The proposed PCFs also realized better visualization of echoes from a diffuse scattering medium than the conventional PCF. [ABSTRACT FROM AUTHOR]