Ultrasonic synthetic aperture imaging algorithm based on power sample entropy as adaptive weight

Phased Coherence Factor (PCF) and General Coherence Factor (GCF) algorithms can enhance the quality of ultrasound imaging, by means of weighting on the results derived from beamforming algorithm. These weighted imaging algorithms have some drawbacks, such as that the brightness of tissue background is reduced, the contrast is not high, and imaging intensity of distant target is declined. The ultrasonic synthetic aperture imaging algorithm based on power sample entropy (PSampen) is proposed. The low-quality imaging results transmitted by a single aperture, can be treated as one element, and a spacial vector can be formed according to the aperture location information. The randomness of spacial vector that corresponds to different imaging points is different and this randomness can be characterized by PSampen, so the PSampen of each spacial vector is calculated as the adaptive weight. Field II simulation results demonstrated that the imaging contrast and resolution based on our proposed method could be effectively improved compared with the traditional DAS. Compared with the PCF and GCF, the tissue background brightness will not be lost. Besides, the quality of ultrasound image is improved.