使用高分辨率相干因子加权技术改善线性阵列光声成像中的图像质量。
Image improvement in linear-array photoacoustic imaging using high resolution coherence factor weighting technique.
作者信息
Mozaffarzadeh Moein, Makkiabadi Bahador, Basij Maryam, Mehrmohammadi Mohammad
机构信息
Research Center for Biomedical Technologies and Robotics, Institute for Advanced Medical Technologies, Tehran, Iran.
Department of Imaging Physics, Laboratory of Acoustical Wavefield Imaging, Delft University of Technology, Delft, Netherlands.
出版信息
BMC Biomed Eng. 2019 Apr 5;1:10. doi: 10.1186/s42490-019-0009-9. eCollection 2019.
BACKGROUND
In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF.
RESULTS
The higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 , in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively.
CONCLUSION
Proposed method provides a high resolution along with a low level of sidelobes for PAI.
背景
在光声成像（PAI）中，由于实现简单，最常用的波束形成算法是延迟求和（DAS）。然而，它会产生受高旁瓣水平影响的低质量图像。相干因子（CF）可用于解决DAS重建图像中的旁瓣问题，但与最小方差（MV）等高分辨率波束形成器相比，分辨率提高得还不够好。本文提出使用高分辨率相干因子（HRCF）加权技术，即在传统CF公式中用MV代替现有的DAS。
结果
通过数值和实验证明了HRCF具有更高的性能。模拟得到的定量结果表明，在40深度处，与DAS+CF和MV+CF相比，HRCF分别将半高宽提高了约91%和15%，将信噪比提高了约40%和14%。
结论
所提出的方法为PAI提供了高分辨率和低旁瓣水平。
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