Compressed beamforming with applications to ultrasound imaging

Abstract

Recent developments in medical treatment put challenging demands on ultrasound imaging systems. These demands typically imply increasing the number of transducer elements involved in each imaging cycle. Confined to traditional sampling methods, the inevitable result is a significant growth in the amount of raw data that needs to be transmitted from the system front end, and then processed by the processing unit, effecting machinery size and power consumption. In this paper, we derive a scheme which reduces the amount of transmitted data, by applying Compressed Sensing (CS) techniques to analog ultrasound signals detected in the transducer elements. We follow the spirit of Xampling, which combines classic methods from sampling theory with recent developments in CS, aimed at sampling analog signals far below the Nyquist rate. Our scheme enhances SNR, by integrating low-rate samples extracted from multiple transducer elements. We refer to this process as “beamforming in the compressed domain”, or “compressed beamforming”.