An Adaptive Synthetic Aperture Method Applied to Ultrasound Tissue Harmonic Imaging
- PMID: 29610086
- DOI: 10.1109/TUFFC.2018.2799870
An Adaptive Synthetic Aperture Method Applied to Ultrasound Tissue Harmonic Imaging
Abstract
In recent years, the minimum variance (MV) beamformer has been highly regarded since it provides high resolution and contrast in B-mode ultrasound imaging compared with nonadaptive delay-and-sum (DAS) beamformer. However, the performance of MV beamformer is degraded in the presence of the noise due to inaccurate estimation of the covariance matrix resulting in low-quality images. The conventional tissue harmonic imaging (THI) offers multiple advantages over conventional pulse-echo ultrasound imaging, including enhanced contrast resolution and improved axial and lateral resolutions, but low signal-to-noise ratio (SNR) is a major problem facing this imaging method, which uses a fixed transmit focus and dynamic receive focusing (DRF). In this paper, a synthetic aperture method based on the virtual source, namely, bidirectional pixel-based focusing (BiPBF), has been combined with the MV beamformer and then applied to second-harmonic ultrasound imaging. The main objective is suppressing the noise level to enhance the performance of the MV beamformer in the harmonic imaging, especially in lower and deeper depths where the SNR is low. In addition, combining the BiPBF and MV weighting results in simultaneous improvement in imaging resolution and contrast, in comparison with the conventional methods: DRF (DAS), BiPBF (DAS), and DRF (MV). The performance of the proposed method is evaluated on simulated and experimental RF data. The THI is achieved using the pulse-inversion technique. The results of the simulated wire phantom demonstrate that the proposed beamformer can achieve the best lateral resolution, along different depths, compared with DRF (DAS), BiPBF (DAS), and DRF (MV) methods. The results of the simulated and experimental cyst phantoms show that the new beamformer improves the contrast ratio (CR) and contrast-to-noise ratio (CNR) of the resulting images. In results of simulated cyst phantom, in average, the new beamformer improves the CR and CNR of the cyst about (7.4 dB, 49%), (3.2 dB, 16%), and (5 dB, 26%) compared with DRF (DAS), BiPBF (DAS), and DRF (MV), respectively. In results of experimental cyst phantom, these relative improvements are about (4.2 dB, 22%), (1.7 dB, 7%), and (2.6 dB, 15%). In addition, BiPBF (MV) method offers improved edge definition of cysts in comparison with the other methods.
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