IEEE Trans Ultrason Ferroelectr Freq Control. 2021 Apr;68(4):969-978. doi: 10.1109/TUFFC.2020.3027956. Epub 2021 Mar 26.
This article addresses the problem of high-resolution Doppler blood flow estimation from an ultrafast sequence of ultrasound images. Formulating the separation of clutter and blood components as an inverse problem has been shown in the literature to be a good alternative to spatio-temporal singular value decomposition (SVD)-based clutter filtering. In particular, a deconvolution step has recently been embedded in such a problem to mitigate the influence of the point spread function (PSF) of the imaging system. Deconvolution was shown in this context to improve the accuracy of the blood flow reconstruction. However, the PSF needs to be measured experimentally, and measuring it requires nontrivial experimental setups. To overcome this limitation, we propose herein a blind deconvolution method able to estimate both the blood component and the PSF from Doppler data. Numerical experiments conducted on simulated and in vivo data demonstrate qualitatively and quantitatively the effectiveness of the proposed approach in comparison with the previous method based on experimentally measured PSF and two other state-of-the-art approaches.
本文解决了从超快序列超声图像中估计高分辨率多普勒血流的问题。文献表明，将杂波和血流分量的分离表述为一个反问题是一种替代基于时空奇异值分解（SVD）的杂波滤波的好方法。特别是，最近在这样的问题中嵌入了反卷积步骤，以减轻成像系统点扩散函数（PSF）的影响。在这种情况下，反卷积被证明可以提高血流重建的准确性。然而，PSF 需要通过实验来测量，并且测量它需要复杂的实验设置。为了克服这一限制，我们提出了一种盲反卷积方法，能够从多普勒数据中同时估计血流分量和 PSF。在模拟和体内数据上进行的数值实验定性和定量地证明了与基于实验测量 PSF 的先前方法以及其他两种最先进的方法相比，所提出的方法的有效性。
