Plane wave ultrasound imaging using compressive sensing and minimum variance beamforming

Ultrafast Plane Wave Imaging Using Tensor Completion-Based Minimum Variance Algorithm.

Image quality improvement in single plane-wave imaging using deep learning

BACKGROUND: The coherent plane wave compounding (CPWC) is a promising technique to enhance the imaging quality while maintaining the high frame rate in the plane wave ultrasound imaging. Recently, the spatial-coherence-based method has been specially designed to process echo matrix required by the minimum variance (MV) method.OBJECTIVE: In this paper, a novel beamforming method that integrates the submatrix-spatial-coherence-based MV with the sign coherence factor (SCF) is proposed to further improve the imaging quality.METHOD: The submatrix smoothing technique is modified to smooth and de-correlate signals of the receiving array dimension. Then, the SCF is used to modify the input vector of the beamformer, which can reduce side lobe noises with almost no increase in the amount of calculation. Simulation, phantom, in vivo, and sound velocity error experiments have been performed to verify the superiority of the proposed beamformer.RESULTS: The imaging results show that the proposed approach performs better in the imaging resolution and contrast compared to the traditional CPWC method.CONCLUSION: The robustness of the proposed method is enhanced, and the over-suppression phenomenon can be alleviated, which is a phenomenon that occurs in the original spatial-coherence and SCF methods.

Synthetic aperture focusing based on planar waves also known as coherent plane wave compounding (CPWC) was introduced to reduce the diffraction spreading effect of ultrasound at depths (Song et al. US Patent 6736780, 2004). CPWC has been widely used in shear wave elasticity imaging due to its capability of ultrafast frame rate (Montaldo, et al. IEEE TUFFC, vol. 56, 2009). However, CPWC based on unfocused (plane waves) or defocused Tx beams has an inherent limitation in imaging wider field of view (FOV) due to the use of sampling angle in transmitting steered ultrasound wave. The sampling angle causes an unwanted side-lobe artifact if the sampling interval of angle is not small enough to cancel the artifact.

Plane wave (PW) imaging is fast, but limited by poor imaging quality. Coherent PW compounding (CPWC) improves image quality but decrease frame rate. In this study, we propose a modified CycleGAN model that combines a residual attention module with a space-frequency dual-domain discriminator, termed RADD-CycleGAN, to rapidly reconstruct high-quality ultrasound images. To enhance the ability to reconstruct image details, we specially design a process of hybrid dynamic and static channel selection followed by the frequency domain discriminator. The low-quality images are generated by the 3-angle CPWC, while the high-quality images are generated as real images (ground truth) by the 75-angle CPWC. The training set includes unpaired images, whereas the images in the test set are paired to verify the validity and superiority of the proposed model. Finally, we respectively design ablation and comparison experiments to evaluate the model performance. Compared with the basic CycleGAN, our proposed method reaches a better performance, with a 7.8% increase in the peak signal-to-noise ratio and a 22.2% increase in the structural similarity index measure. The experimental results show that our method achieves the best unsupervised reconstruction from low quality images in comparison with several state-of-the-art methods.

Plane-wave imaging (PWI) is a best way to improve the frame rate in ultrasound imaging. However, due to the lack of transmit focus in PWI, the image quality is poor. A novel coherent plane-wave compounding (CPWC) was proposed to handle this issue, but the increased plane waves (PWs) reduced the frame rate. Thus, we combine a novel Double-Stage Delay Multiply and Sum (DS-DMAS) beamformer, which is shown to be better to improve the image quality, with plane-wave compounding to analyze the performance in terms of resolution and contrast. The simulation tests are carried out to show that applying DS-DMAS beamformer can achieve better results even if the number of transmitted PWs are decreased.

The image quality provided by current ultrasound (US) scanners can be increased by extending the effective bandwidth of the US transducers. In 2007, a promising technique, called Resolution Enhancement Compression (REC), was proposed. Combining chirp modulated signals in emission and Modified Wiener Filters (MTF) in reception, REC allows bandwidth enhancement by boosting the energy of the emitted/received signal in the frequency bands where the transducer operates inefficiently. In this paper the first implementation of REC on a research ultrasound scanner using a Capacitive Micromachined Ultrasonic Transducer (CMUT) is presented, the objective being to increase the quality of the images obtained using a Coherent Plane Wave Compounding (CPWC) beamforming technique. The experimental results acquired on wire and cyst phantom indicate a clear increase of the image quality in terms of axial/lateral resolution and signal/contrast to noise ratio. This paper thus proves that REC is capable to yield very good results when implemented on broadband ultrasound transducers.

Coherent plane wave compounding (CPWC) reconstructs transmit focusing by coherently summing several low-resolution plane-wave (PW) images from different transmit angles to improve its image resolution and quality. The high frame rate of CPWC imaging enables a much larger number of Doppler ensembles such that the Doppler estimation of blood flow becomes more reliable. Due to the unfocused PW transmission, however, one major limitation of the Doppler estimation in CPWC imaging is the relatively low signal-to-noise ratio (SNR). Conventionally, the Doppler power is estimated by a zero-lag autocorrelation which reduces the noise variance, but not the noise level. A higher-lag autocorrelation method such as the first-lag (R(1)) power Doppler image has been developed to take advantage of the signal coherence in the temporal direction for suppressing uncorrelated random noises. In this paper, we propose a novel Temporal Multiply-and-Sum (TMAS) power Doppler detection method to further improve the noise suppression of the higher-lag method by modulating the signal coherence among the temporal correlation pairs in the higher-lag autocorrelation with a tunable pt value. Unlike the adaptive beamforming methods which demand for either receive–channel–domain or transmit–domain processing to exploit the spatial coherence of the blood flow signal, the proposed TMAS power Doppler can share the routine beamforming architecture with CPWC imaging. The simulated results show that when it is compared to the original R(1) counterpart, the TMAS power Doppler image with the pt value of 2.5 significantly improves the SNR by 8 dB for the cross-view flow velocity within the Nyquist rate. The TMAS power Doppler, however, suffers from the signal decorrelation of the blood flow, and thus, it relies on not only the pt value and the flow velocity, but also the flow direction relative to the geometry of acoustic beam. The experimental results in the flow phantom and in vivo dataset also agree with the simulations.

A new approach to implement minimum variance distortionless response (MVDR) beamforming is introduced for coherent plane-wave compounding (CPWC). MVDR requires the covariance matrix of the incoming signal to be estimated and a spatial smoothing approximation is usually adopted to prevent this calculation from being underconstrained. In the new approach, we analyze MVDR as a spatial filter that decorrelates signals received at individual channels before summation. Based on the analysis, we develop two MVDR beamformers without using any spatial smoothing. First, MVDR weights are applied to the received signals after accumulating the data over transmits at different angles, while the second involves weighting the data collected in individual transmits and compounding over the transducer elements. In both cases, the covariance matrix is estimated using a set of slightly different combinations of the echo data. We show the sufficient statistic for this estimation that can be described by approximating the correlation among the backscattered ultrasound signals to their spatial coherence. Using the van Cittert-Zernike theorem, their statistical similarity is assessed by relating the spatial coherence to the profile of the source intensity. Both spatial-coherence-based MVDR beamformers are evaluated on data sets acquired from simulation, phantom, and in vivo studies. Imaging results show that they offer improvements over simple coherent compounding in terms of spatial and contrast resolutions. They also outperform other existing MVDR-based methods in the literature that are applied to CPWC.

Ultrasound elastography is used to characterize biomechanics of the tissue using motion estimations. A non-rigid model is likely more suitable to characterize complex tissue motions. In this paper, we proposed a modified affine phase-based estimator (APBE) on the application of cross-sectional noninvasive vascular elastography (NIVE). Considering coherent plane wave compounding (CPWC) and TO imaging, CPWC&TO images were obtained. And a time-ensemble approach and an incompressibility constraint were introduced into the original APBE. In the simulation study, the modified APBE provided the least estimation error. For in vitro experiments, the modified APBE provided the higher signal-to-noise ratio (SNR) for a homogeneous phantom. For a heterogeneous phantom with a soft inclusion, the modified APBE provided the higher SNR and contrast-to-noise ratio (CNR). Overall, the performance of the modified APBE outperformed the original APBE.

Ultrasound imaging plays a critical role in diagnostics in biomedicine because of its safety, nature, and low cost. Conventional ultrasound systems form images using a focused beam during transmission and dynamic focusing during the reception. The area under examination can be simultaneously insonified using a plane wave, which allows for ultrafast data capture rates but lowers image quality. The resultant image can be improved by coherent plane-wave compounding, in which numerous plane waves are released at different angles to produce distinct image datasets that are then blended to improve the final composite image. This study used the Fourier-domain technique for coherent plane-wave compounding image reconstruction from the image produced by conventional ultrasound to investigate the quality of the image produced compared to the X-ray image. To establish the merits and limitations of this approach, the researchers provided quantitative comparisons with the images obtained by the X-ray machine. The evaluation results are based on the peak signal-to-noise ratio (PSNR), mean, and variance. The results obtained showed that the migration method can precisely image the cortical bone fracture and offer good contrast between the bone tissue and the subcutaneous tissues.

To prospectively compare iopamidol 370, which is a low-osmolar contrast medium and iodixanol 320, which is an iso-osmolar contrast medium, in terms of image quality and nonserious adverse effects that have the potential to influence the image quality in a 16-slice multi-detector row computed tomography coronary angiography. Sixty patients were divided into two groups to receive iodixanol 320 or iopamidol 370. Image quality was assessed, using a five-point grading scale. Differences in the mean attenuation (Hounsfield units) at the origin of the coronary arteries and on the ascending aorta in both the groups were compared. The number and intensity of adverse effects were compared between the two groups. The mean attenuation values of the ascending aorta and the origins of the coronary arteries for the two groups showed no significant difference (P≥0.41). There was no significant difference in terms of image quality between the two groups on all evaluated segments. There was a statistically significant difference in the number of adverse effects (P=0.001) between the two groups. However, in both the iodixanol group and the iopamidol group, there was no significant difference in terms of image quality between the patients with and without adverse effects. The frequency of adverse effects is lower in the iodixanol group than the iopamidol group. Iodixanol 320 can provide both vascular enhancement and image quality, which is similar to iopamidol 370 in a 16-slice multi-detector row computed tomography coronary angiography. There was no significant difference in terms of overall image quality between the patients with and without adverse effects in either of the groups.

Ultrafast imaging modes, such as coherent plane-wave compounding (CPWC), increase image uniformity and reduce grating lobe artifacts by dynamic receive apertures. The focal length and the desired aperture width maintain a given ratio, which is called the F-number. Fixed F-numbers, however, exclude useful low-frequency components from the focusing and reduce the lateral resolution. Herein, this reduction is avoided by a frequency-dependent F-number. This F-number derives from the far-field directivity pattern of a focused aperture and can be expressed in closed form. The F-number, at low frequencies, widens the aperture to improve the lateral resolution. The F-number, at high frequencies, narrows the aperture to avoid lobe overlaps and suppress grating lobes. Phantom and in-vivo experiments with a Fourier-domain beamforming algorithm validated the proposed F-number in CPWC. The lateral resolution, which was measured by the median lateral full widths at half maximum of wires, improved by up to 46.8% and 14.9% in a wire and a tissue phantom, respectively, in comparison to fixed F-numbers. Grating lobe artifacts, which were measured by the median peak signal-to-noise ratios of wires, reduced by up to 9.9 dB in comparison to the full aperture. The proposed F-number thus outperformed F-numbers that were recently derived from the directivity of the array elements.

Compressed sensing (CS) is a sparse signal sampling methodology for efficiently acquiring and reconstructing a signal from relatively few measurements. Recent work shows that CS is well-suited to be applied to problems in genomics, including probe design in microarrays, RNA interference (RNAi), and taxonomic assignment in metagenomics. The principle of using different CS recovery methods in these applications has thus been established, but a comprehensive study of using a wide range of CS methods has not been done. For each of these applications, we apply three hitherto unused CS methods, namely, l1-magic, CoSaMP, and l1-homotopy, in conjunction with CS measurement matrices such as randomly generated CS m matrix, Hamming matrix, and projective geometry-based matrix. We find that, in RNAi, the l1-magic (the standard package for l1 minimization) and l1-homotopy methods show significant reduction in reconstruction error compared to the baseline. In metagenomics, we find that l1-homotopy as well as CoSaMP estimate concentration with significantly reduced time when compared to the GPSR and WGSQuikr methods.

Recently, adaptive beamforming methods have been successfully applied to medical ultrasound imaging, resulting in significant improvement in image quality compared to non-adaptive delay-and-sum (DAS) beamformer. Most of the adaptive beamformers presented in the ultrasound imaging literature are based on the minimum variance (MV) beamformer which can improve the imaging resolution while retaining the contrast. The main objective of this research is to present a beamformer which could improve the imaging resolution and contrast, at the same time. In this paper, we have applied the eigenspace-based MV (EIBMV) beamformer to medical ultrasound imaging and shown the simultaneous improvement in imaging resolution and contrast. EIBMV beamformer utilizes the eigenstructure of the covariance matrix to enhance the performance of the MV beamformer. The weight vector of the EIBMV is found by projecting the obtained MV weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix. EIBMV beamformer shows a significant reduction in the sidelobe levels while representing the same mainlobe width as the MV. Specifically, in the point targets phantom, the proposed method decreases the sidelobes about 22 dB and 29 dB compared to MV and DAS, respectively. Furthermore, the proposed method increases the contrast of simulated cyst phantom about 8.6 dB and 14.1 dB and also improves the contrast-to-noise ratio about 31% and 61%, compared to MV and DAS, respectively.