Image enhancement in ultrasound passive cavitation imaging using centroid and flatness of received channel data

Passive cavitation imaging method is used to observe the ultrasonic waves generated when a group of bubbles collapses. A problem with passive cavitation imaging is a low resolution and large side lobe levels. Since ultrasound signals generated by passive cavitation take the form of a pulse, the amplitude distribution of signals received across the receive channels varies depending on the direction of incidence. Both the centroid and flatness were calculated to determine weights at imaging points in order to discriminate between the main and side lobe signals from the signal amplitude distribution of the received channel data and to reduce the side lobe levels. The centroid quantifies how the channel data are distributed across the receive channel, and the flatness measures the variance of the channel data. We applied the centroid weight and the flatness to the passive cavitation image constructed using the delay-and-sum focusing and minimum variance beamforming methods to improve the image quality. Using computer simulation and experiment, we show that the application of weighting in delay-and-sum and minimum variance beamforming reduces side lobe levels.