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This paper addresses the problem of high-resolution Doppler blood flowestimation from an ultrafast sequence of ultrasound images. Formulating theseparation of clutter and blood components as an inverse problem has been shownin the literature to be a good alternative to spatio-temporal singular valuedecomposition (SVD)-based clutter filtering. In particular, a deconvolutionstep has recently been embedded in such a problem to mitigate the influence ofthe experimentally measured point spread function (PSF) of the imaging system.Deconvolution was shown in this context to improve the accuracy of the bloodflow reconstruction. However, measuring the PSF requires non-trivialexperimental setups. To overcome this limitation, we propose herein a blinddeconvolution method able to estimate both the blood component and the PSF fromDoppler data. Numerical experiments conducted on simulated and in vivo datademonstrate qualitatively and quantitatively the effectiveness of the proposedapproach in comparison with the previous method based on experimentallymeasured PSF and two other state-of-the-art approaches.

Joint Blind Deconvolution and Robust Principal Component Analysis for Blood Flow Estimation in Medical Ultrasound Imaging