Abstract
This paper estimates the side lobe levels from the received echo data, and proposes and compares three types of filters that can be used to suppress them in an ultrasound image. Ultrasound echo signals from the off-axis scatterers can be modeled as a sinusoidal wave whose spatial frequency in the lateral direction of a transducer array varies as a function of the incident angle. The received channel data waveform due to side lobes have a spatial frequency of an integer plus a half. Doubling the length of the channel data by appending zeros and taking the discrete Fourier transform of the elongated data makes the spatial frequency of the channel data due to side lobes become an integer. Thus, it is possible to estimate the complex amplitude of the side lobes. Adding together all the channel data of the estimated side lobes, we can obtain the side lobe levels present in ultrasound field characteristics. We define the summed value as a quality factor that is used as a parameter of side lobe suppression filters. Computer simulations as well as experiments on wires in a water tank and a cyst phantom show that the proposed filters are very effective in reducing side lobe levels and that the amount of computation is smaller than that of the minimum variance beamforming method while showing comparable performance. A method of estimating and suppressing side lobes in an ultrasound image is presented, and the performance of the proposed filters is found to be viable against the conventional B-mode imaging and minimum variance beamforming methods.
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This work was supported by the Daejin University Research Grants in 2016.
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Kwon SJ declares that he has no conflict of interest in relation to the work in this article. Jeong MK declares that he has no conflict of interest in relation to the work in this article.
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Kwon, S.J., Jeong, M.K. Estimation and suppression of side lobes in medical ultrasound imaging systems. Biomed. Eng. Lett. 7, 31–43 (2017). https://doi.org/10.1007/s13534-016-0002-3
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DOI: https://doi.org/10.1007/s13534-016-0002-3