Xampling in Ultrasound Imaging

TL;DR

This paper introduces an Xampling-based compressed sensing approach for ultrasound imaging, significantly reducing data size and sampling rates while maintaining image quality, thus addressing hardware and processing limitations.

Contribution

It applies the Xampling framework to ultrasound signals, enabling efficient data acquisition with lower sampling rates compared to traditional methods.

Findings

Reduced sampling rates while maintaining image quality

Significantly decreased data size in ultrasound imaging

Potential for improved hardware efficiency

Abstract

Recent developments of new medical treatment techniques put challenging demands on ultrasound imaging systems in terms of both image quality and raw data size. Traditional sampling methods result in very large amounts of data, thus, increasing demands on processing hardware and limiting the exibility in the post-processing stages. In this paper, we apply Compressed Sensing (CS) techniques to analog ultrasound signals, following the recently developed Xampling framework. The result is a system with significantly reduced sampling rates which, in turn, means significantly reduced data size while maintaining the quality of the resulting images.