Abstract
A new method to improve the accuracy of 3D cine PC-MR (4D Flow) velocimetry using image restoration technique is proposed. The error of 4D Flow measured data is separated into the Gaussian noise part and the blur part, which consists of the two types of characteristic artifacts: "dragging velocity" and "lower velocity peak". The proposed method models the blur artifacts with a nonlinear point spread function (PSF) for the velocity images. The model parameters of the PSF are determined by inverse analysis with the results of a series of phantom study. And then the accurate velocity images can be estimated using image restoration with the PSF and in vivo measurement images. A validation result shows the volume flow rate (VFR) of the pseudo measurement data given by the PSF agrees with that of the 4D Flow measurement data well and the error is within several percent.
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