Compressed Beamforming in Ultrasound Imaging
Noam Wagner, Yonina C. Eldar, Zvi Friedman

TL;DR
This paper introduces a novel compressed beamforming method that enhances SNR and reduces sampling rates in ultrasound imaging, enabling efficient processing of data from multiple transducer elements.
Contribution
It proposes a new compressed beamforming technique that combines low-rate sampling with SNR enhancement for ultrasound imaging.
Findings
Achieves nearly eight-fold reduction in sample-rate.
Successfully images cardiac tissue perturbations.
Enhances SNR of low-rate ultrasound samples.
Abstract
Emerging sonography techniques often require increasing the number of transducer elements involved in the imaging process. Consequently, larger amounts of data must be acquired and processed. The significant growth in the amounts of data affects both machinery size and power consumption. Within the classical sampling framework, state of the art systems reduce processing rates by exploiting the bandpass bandwidth of the detected signals. It has been recently shown, that a much more significant sample-rate reduction may be obtained, by treating ultrasound signals within the Finite Rate of Innovation framework. These ideas follow the spirit of Xampling, which combines classic methods from sampling theory with recent developments in Compressed Sensing. Applying such low-rate sampling schemes to individual transducer elements, which detect energy reflected from biological tissues, is limited…
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