Due to breathing, heart beat and vessel wall pulsation the tissue surrounding a vessel will experience motion. By simulating this motion along with the motion of the blood, very realistic RF-data can be computed. In this example RF-data for the carotid artery including tissue motion due to breathing and pulsation is generated. The blood velocity profile is modeled using Womersley´s pulsatile flow model.
The phantom generates 3,500 files with positions of scatterers at the corresponding time step. The change in position of the scatterers at each time step is determined by the blood velocity and the tissue motion models. These files are then used for generating the RF-lines along one direction for the number time steps - equal to 3,500. The transducer is modeled as a convex, elevation focused array with 60 elements with a Hanning apodization in transmit and receive. The element height was 15 mm, the width 0.37 mm, and the kerf 0.03 mm. The transmit pulse consist of 8 periods. A single transmit focus was placed at 40 mm, and receive focusing was done at 40 mm intervals.
The resulting signals can then be used in a standard autocorrelation estimator for finding the velocity image.
Plots of a simulated (top) and measured (bottom) RF-signal are given below.
The m-files can be found at:
The routine field.m initializes the field system, and should be modified to point to the directory holding the Field II code and m-files. The routine make_sct.m is then called to make the file for the scatterers in the phantom. The script sim_motion.m is then called. Here the field simulation is performed and the data is stored in RF-files; one for each RF-line done. A data file called velocity.mat contains a matrix with the blood velocities with respect to time and relative distance to center of vessel.
M. Schlaikjer, S.Torp-Pedersen, J.A. Jensen and P.F. Stetson:
Tissue motion in blood velocity estimation and its simulation,
IEEE Ultrasonics Symposium Proceeding, pp. 1495-1499, Volume 2, IEEE, 1998.
and
M. Schlaikjer, S.Torp-Pedersen and J.A. Jensen: Simulation of RF data with tissue motion for optimizing stationary echo canceling filters, Ultrasonics, vol: 41(6), p. 415-419 (2003)