Orthogonal sparse dictionary based on Chirp echo for ultrasound imaging

Abstract

High-end ultrasound imaging system always requires high-speed data acquisition and processing system, which often leads to high-cost issues of ultrasound hardware. Fortunately, the compressed sensing theory offers a perspective of reducing the data sampling rate. To obtain better-reconstructed ultrasound imaging quality at a low sampling rate, this paper explores coding technology with compressed sensing and proposes a kind of Orthogonal Sparse Dictionary based on Chirp echo (OSD). The simulation experiments of scattering point targets, cyst phantoms, and geabr_0 data were conducted, and a series of performance index parameters about reconstructed image quality were calculated and analyzed. The simulation results indicate that the image quality reconstructed by the proposed OSD is superior to traditional sparse dictionaries with the same reconstruction algorithm and sampling rate. By applying the proposed OSD, there is no obvious distortion about the image quality at 30% sampling rate.