PS-10 Optimal Velocity Estimation in Ultrasound Color Flow Imaging in Presence of Clutter Noise

In color flow imaging (CFI), the rejection of tissue clutter signal is treated separately from blood velocity estimation, by high-pass filtering the received Doppler signal. The complete suppression of clutter is then difficult to achieve without affecting the subsequent velocity estimates. In this work a different approach to velocity estimation is investigated, based on a statistical model of the signal from both clutter and blood. An analytic expression for the Cramer-Rao lower bound (CRLB) is developed, and used to determine the existence of an efficient maximum likelihood estimator (MLE) of blood velocity, when assuming full knowledge of the clutter statistics. We further simulate and compare the performance of the MLE to that of the autocorrelation method (ACM) using different clutter filters. Two signal scenarios are simulated, representing moderate and excessive clutter conditions respectively. Simulations showed that by including 3-9 independent spatial points, the MLE variance approached the CRLB in both scenarios. The MLE showed a substantial reduction in bias and variance compared to the ACM, which only became unbiased for moderate clutter conditions, then with a variance of up to four times the CRLB. Due to long clutter filter transition regions, much performance can especially be gained for low blood velocities by incorporating a clutter signal model in model-based estimators