title: Evaluating the robustness of dual apodization with cross-correlation.
abstract: We have recently presented a new method to suppress side lobes and clutter in ultrasound imaging called dual apodization with cross-correlation (DAX). However, due to the random nature of speckle, artifactual black spots may arise with DAX-processed images. In this paper, we present one possible solution, called dynamic DAX, to reduce these black spots. We also evaluate the robustness of dynamic DAX in the presence of phase aberration and noise. Simulation results using a 5 MHz, 128-element linear array are presented using dynamic DAX with aberrator strengths ranging from 25 ns root-mean-square (RMS) to 45 ns RMS and correlation lengths of 3 mm and 5 mm. When simulating a 3 mm diameter anechoic cyst, at least 100% improvement in the contrast-to-noise ratio (CNR) compared with standard beamforming is seen using dynamic DAX, except in the most severe case. Layers of pig skin, fat, and muscle were used as experimental aberrators. Simulation and experimental results are also presented using dynamic DAX in the presence of noise. With a system signal-to-noise ratio (SNR) of at least 15 dB, we have a CNR improvement of more than 100% compared with standard beamforming. This work shows that dynamic DAX is able to improve the contrast-to-noise ratio reliably in the presence of phase aberration and noise.
authors.affiliation: University of Southern California, Biomedical Engineering, Los Angeles, CA, USA. chiseo@usc.edu
authors.forename: Chi Hyung
authors.initials: CH
authors.lastname: Seo
authors.forename: Jesse T
authors.initials: JT
authors.lastname: Yen
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D003560:Cysts / Q000000981:diagnostic imaging; D007089:Image Enhancement / Q000379:methods*; D009132:Muscles / Q000000981:diagnostic imaging; D016011:Normal Distribution; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D012867:Skin / Q000000981:diagnostic imaging; D013552:Swine; D014463:Ultrasonography