论文标题
在光声成像中基于高阶相关的实时波束形成
Higher-order correlation based real-time beamforming in photoacoustic imaging
论文作者
论文摘要
基于线性阵列的光声图像是使用常规的延迟和光束形成方法重建的。尽管DAS波束形成器非常适合PA图像形成，但由于PA信号相关性的不准确假设，重建的图像通常受到噪音，旁观和其他强烈的伪影的困扰。这项工作旨在开发一种倒置方法，以减少旁观和工件的发生并改善图像质量性能。我们基于高阶信号相关性提出了一种新型的波束形式，其中比传统的延迟延迟 - 延迟 - 多层和sum（DMA）组合和总结了更多的延迟PA信号。与传统的波束形式相比，该提出的技术可有效改进分辨率，对比度和SNR。此方法中的计算复杂性缩小到das $ o（n）$的相同顺序。因此，可以在实时PA图像重建中实现此波束形式。对计算时间进行了基于GPU的研究。建议的方法几乎在DAS和实时DMA的同一时间范围内执行。对算法的验证研究都是在数值和实验上完成的。在所有情况下，高阶DMA光束形成器均显示出优质的重建。对Ex-Vivo幻影的定量评估表明，与DAS和DMA相比，SNR的FWHM提出的FWHM提高了51％和6％。最终，在实时光声成像及其应用中，提出的算法具有很大的潜力和有希望的。
Linear-array based photoacoustic images are reconstructed using the conventional delay-and-sum (DAS) beamforming method. Although the DAS beamformer is well suited for PA image formation, reconstructed images are often afflicted by noises, sidelobes, and other intense artifacts due to inaccurate assumptions of PA signal correlation. The work aims to develop an inversion method that reduces the occurrence of sidelobes and artifacts and improves image quality performance. We present a novel beamformer based on higher-order signal correlation, where more number of delayed PA signals are combined and summed up than the conventional delay-multiply-and-sum (DMAS). The proposed technique provides efficient improvements in resolution, contrast, and SNR compared to the traditional beamformers. Computational complexity in this method is shrunk to the same order of DAS $O(N)$. Therefore, this beamformer can be implemented in real-time PA image reconstruction. A GPU based study was performed on computation time. Proposed method almost executes in the same time frame of DAS and real-time DMAS. A validation study of the algorithm was accomplished both numerically and experimentally. Higher-order DMAS beamformers demonstrate superior reconstruction in all cases. The quantitative evaluation of the ex-vivo phantom shows that the proposed method leads to 51% and 6% improvement in FWHM, 81% and 39% improvement in SNR compared to DAS and DMAS, respectively. Conclusively, the proposed algorithm is very much potential and promising in real-time photoacoustic imaging and its applications.
