  This paper 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 experimentally measured point spread function (PSF) of the imaging system.
Deconvolution was shown in this context to improve the accuracy of the blood
flow reconstruction. However, measuring the PSF requires non-trivial
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.
