An ultrasound imaging algorithm combining optimal apodization function and multi-parameter composite conditional factor

The coherence factor of a single parameter is difficult to simultaneously improve the resolution and contrast of ultrasound images in complex imaging scenarios. Therefore, an ultrasound imaging algorithm combining optimal apodization function and multi-parameter composite conditional factor (OA-MCCF) is proposed to improve the overall image quality. Firstly, several sets of apodization window functions are weighted on the received echo signals, and the optimal apodization function is selected based on the principle of minimizing the variance of the beamformer output. Secondly, the selected apodization function is weighted onto the echo signals to obtain the optimized array signals, and the current conditional coherence is calculated by the signals at multiple sampling times. Finally, the weighted factor is obtained by composing the conditional factors with multiple parameters according to the global image coherence information. The simulated and experimental results demonstrate that, compared with the traditional delay-and-sum (DAS) algorithm, the proposed OA-MCCF algorithm can significantly enhance image resolution and contrast. Specifically, the OA-MCCF can achieve the greatest improvements in full width at half maximum (FWHM) of 89.23% in the point-target simulation and 63.22% in the carotid longitudinal-section experiment. Compared with the traditional coherence factor algorithm, the proposed algorithm improves resolution performance while maintaining image contrast.