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• An ADCPMV-TSF beamformer is proposed by a constraint matrix projection operator and adaptive threshold for ultrasound imaging. • The proposed constraint matrix projection can further improve the resolution. • The threshold decomposition function is implemented to eliminate dark-area artifacts. • The proposed methods have obvious improvement in resolution and robustness than traditional ESBMV. The eigenspace-based minimum variance (ESBMV) beamformer can enhance the contrast of the minimum variance (MV), but the traditional orthogonal projection and fixed eigen-decomposition threshold make it difficult to obtain further improvement in resolution and speckle uniformity. In this paper, a constraint matrix projection minimum variance based on adaptive decomposition threshold (ADCPMV) is proposed for ultrasound imaging, which aims to improve the insufficiency of ESBMV. Firstly, a constraint matrix with direction information is put forward to better remove the interference and noise of MV weight. Then, a threshold decomposition function based on truncated smoothed coherence factor (TSF) is proposed to eliminate dark-area artifacts. Finally, the TSF is used as the weighting to improve the ADCPMV contrast. Simulations and the experimental datasets of ats_wires , geabr_0 and rat_tumor are introduced to inspect the performance of the proposed algorithms. The result of point target simulation shows that the full-width at half-maximum (FWHM) of ADCPMV-TSF is reduced by 93.98% and 80.19% than that of traditional delay-and-sum (DAS) and ESBMV respectively. Furthermore, the geabr_0 experimental result shows that compared with traditional DAS and ESBMV, the FWHM of ADCPMV-TSF is improved by 87.74% and 61.19% respectively. Meanwhile, the proposed ADCPMV-TSF can well avoid the generation of dark-area artifacts and get the maximal improvement of speckle signal-to-noise ratio is 103.57%. [ABSTRACT FROM AUTHOR]

• A low complexity adaptive beamformer combined with improved multiphase apodization with cross-correlation is proposed. • A new phase apodization is proposed to further suppress clutter. • The echo signal apodized by LCA is used as input for phase apodization to improve resolution. • This method can significantly improve both resolution and contrast, and has good robustness to noise. • This method involves only a few numerical operations, and it is expected to be applied in real-time imaging systems. In this paper, an ultrasound imaging method combined with low-complexity adaptive beamformer (LCA) and improved multiphase apodization with cross-correlation (IMPAX) is proposed to improve image resolution and contrast with low hardware cost. Firstly, the delayed echo signal is apodized by the LCA to obtain a narrow mainlobe width echo signal and LCA output. Then, multiple pairs of complementary square-wave phase apodizations are applied to the apodized echo signal to obtain corresponding signal pairs, which are used to calculate the normalized cross-correlation (NCC) matrix. Finally, the average value of the NCC matrices is filtered by 2-D means, and the filtered result is introduced as the weighting factor for the LCA output. The simulation and experimental results show that the proposed LCA-IMPAX can effectively reduce the mainlobe width, suppress clutter, and be robust to noise. Compared with DAS, LCA, and MPAX, for simulated point targets, the full-width at half-maximum (FWHM, −6dB) of LCA-IMPAX is reduced by 49.22%, 10.06%, and 48.67%, respectively. For simulated cyst, the CR is improved by 219.91%, 138.08%, and 103.44%, respectively. For experimental cysts, the CR is improved by an average of 145.00%, 136.14%, and 55.09%, respectively. The results of human heart data indicate that LCA-IMPAX has good imaging quality in vivo. Since the proposed method does not involve covariance matrix inversion, it can be applied in real-time imaging systems. [ABSTRACT FROM AUTHOR]

Ultrasound plane-wave imaging has the advantage of high frame rate in addition to high data volume. High data sampling rates and large amounts of data storage can become bottlenecks in ultrasound system design. Although compressed sensing technology can help reduce the burden of sampling and transmission, it achieves relatively low image quality because of its reliance solely on signal sparsity. Therefore, we proposed reconstructing the ultrasound signal by applying additional prior knowledge, such as plane-wave imaging and its echo characteristics. Inspired by multi-hypothesis prediction methods in video compression coding, the plane-wave multi-hypothesis prediction compressed sensing reconstruction method was proposed to improve the accuracy of reconstructions. We applied multi-hypothesis prediction and residual reconstruction on the plane wave to enhance the quality of reconstruction and correct predicted values. Also, to acquire high-quality hypotheses, two hypothesis acquisition schemes were evaluated, constructing search windows on both preceding and subsequent frames as well as the reference frame. Compared with traditional reconstruction methods that rely on sparsity, multi-hypothesis prediction compressed sensing methods can reduce signal reconstruction errors and significantly eliminate image artifacts. Furthermore, by using improved hypotheses, signal reconstruction and image quality can be enhanced, resulting in higher contrast. Comparative simulation experimental results based on the publicly available Plane-Wave Imaging Challenge in Medical Ultrasound (PICMUS) and acoustic radiation force imaging data sets demonstrate that the proposed method outperforms other methods in both reconstruction errors and image quality. This helps to reduce the complexity of sampling and transmission of the ultrasound system. [ABSTRACT FROM AUTHOR]