A Method for Improving Signal-to-Noise Ratio of Tissue Harmonic Imaging Based on Bayesian Inference Using Information of Fundamental Echoes

A medical ultrasound imaging technique with a high spatial resolution and a high signal-to-noise ratio (SNR) is strongly required for precise diagnosis. To obtain high-resolution images, tissue harmonic imaging (THI) can be effectively adopted because of its wide bandwidth characteristics compared with fundamental imaging. However, the amplitude of harmonic components is much smaller than that of a fundamental component. Additionally, frequency dependent attenuation is severe, especially for harmonic components. These phenomena mean that THI is susceptible to noise. From these considerations, in this study, we propose a method for improving the SNR of THI by reducing noise using a signal processing technique. The proposed method is constructed based on the Bayesian inference using fundamental components of echoes, and it can hold the high-resolution nature of THI. We show the effectiveness of the proposed method through simulations. (C) 2012 The Japan Society of Applied Physics