Pre- and post-processing filters for improvement of blood velocity estimation

The standard deviation on the blood velocity estimates are influenced by measurement noise, velocity spread, and signal alteration introduced by de-noising and clutter filters. A noisy and non-smooth appearance of the velocity distribution is obtained, which is not consistent with the actual velocity in the vessels. Post-processing is beneficial to obtain an image that minimizes the variation, and present the important information to the clinicians. Applying the theory of fluid mechanics introduces restrictions on the variations possible in a flow field. Neighboring estimates in time and space should be highly correlated, since transitions should occur smoothly. This idea is the basis of the algorithm developed in this study. From Bayesian image processing theory an a posteriori probability distribution for the velocity field is computed based on constraints on smoothness. An estimate of the velocity in a given point is computed by maximization of the probability, given prior knowledg..

Tissue motion in blood velocity estimation and its simulation

Determination of blood velocities for color flow mapping systems involves both stationary echo canceling and velocity estimation. Often the stationary echo canceling filter is the limiting factor in color flow mapping and the optimization and further development of this filter is crucial to the improvement of color flow imaging. Optimization based on in-vivo data is difficult since the blood and tissue signals cannot be accurately distinguished and the correct extend of the vessel under investigation is often unknown. This study introduces a model for the simulation of blood velocity data in which tissue motion is included. Tissue motion from breathing, heart beat, and vessel pulsation were determined based on in-vivo RF-data obtained from 10 healthy volunteers. The measurements were taken at the carotid artery at one condition and in the liver at three conditions. Each measurement was repeated 10 times to cover the whole cardiac cycle and a total of 400 independent RF measurements of..