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Wavelet Shrinkage-based Adaptive Compounding for Improvement of SNR in High Volume-rate Ultrasound Imaging

机译:基于小波收缩的自适应复合,可提高高倍率超声成像中的信噪比

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High-speed acquisition of ultrasound volume data is needed for fetal cardiac diagnosis. The heartbeat of healthy fetus is 120-160 times per second. Therefore, the acquiring method based on plane wave compounding has been developed to achieve both volume rate and image quality. However, in the conventional plane wave compounding method, the sufficient image quality couldn't be obtained when the acquiring speed is about 150 volumes per second. Compressed Sensing has been applied to improve the image quality and reduce the number of compounding in the previous work [1]. but huge memory (458GB) is required. In this paper, we propose a method to acquire high quality volume image at high-speed with reasonable hardware resources. The basic concept is to improve the image quality of each plane wave image before compounding by simple signal processing. Generally, the acoustic noise of plane wave image generated by the diffraction depends on the steering angle. In our method, the acoustic noise is adaptively reduced depending on the steering angle, and the wavelet shrinkage [2] is used as a basic noise reduction algorithm. In the experimental results, the acoustic noise is reduced by 22dB with only 20MB memory usage for radio frequency simulation data. As a result, we achieved high-speed data acquisition of 167 volumes per second.
机译:胎儿心脏诊断需要高速采集超声量数据。健康胎儿的心跳为每秒120-160次。因此,已经开发了基于平面波合成的获取方法以实现体积率和图像质量两者。但是,在传统的平面波合成方法中,当获取速度约为每秒150个体积时,无法获得足够的图像质量。在以前的工作中,已使用压缩传感来改善图像质量并减少复合次数[1]。但需要巨大的内存(458GB)。在本文中,我们提出了一种在合理的硬件资源下高速获取高质量体图像的方法。基本概念是通过简单的信号处理在合成之前改善每个平面波图像的图像质量。通常,由衍射产生的平面波图像的声噪声取决于转向角。在我们的方法中,根据转向角来自适应地降低声音噪声,并且小波收缩[2]被用作基本的降噪算法。在实验结果中,仅射频仿真数据的20MB内存使用就将噪音降低了22dB。结果,我们实现了每秒167卷的高速数据采集。

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