Ultrasound harmonic enhanced imaging using eigenspace-based coherence factor

Tissue harmonic imaging (THI) utilizes harmonic signals generating within the tissue as the result of nonlinear acoustic wave propagation. With inadequate transmitting acoustic energy, THI is incapable to detect the small objects since poor harmonic signals have been generated. In most cases, high transmission energy cannot be guaranteed because of the imaging safety issue or specific imaging modality such as the plane wave imaging (PWI). Discrimination of small point targets such as calcification, however, is particularly important in the ultrasound diagnosis. Few efforts have been made to pursue the THI with high resolution and good small target visibility at the same time. In this paper, we proposed a new eigenspace-based coherence factor (ESBCF) beamformer to solve this problem. A new kind of coherence factor (CF), named as ESBCF, is firstly proposed to detect the point targets. The detected region-of-interest (ROI) is then enhanced adaptively by using a newly developed beamforming method. The ESBCF combines the information from signal eigenspace and coherence factor by expanding the CF to the covariance matrix of signal. Analogous to the image processing but in the radio frequency (RF) data domain, the proposed method fully utilizes the information from the fundamental and harmonic components. The performance of the proposed method is demonstrated by simulation and phantom experiments. The improvement of the point contrast ratio (PCR) is 7.6dB in the simulated data, and 6.0dB in the phantom experiment. Thanks to the improved small point detection ability of the ESBCF, the proposed beamforming algorithm can enhance the PCR considerably and maintain the high resolution of the THI at the same time.