An optimised delay multiply and sum ultrasonic imaging algorithm based on sparse arrays and parallel computing

The Total Focusing Method (TFM) focuses pixels using the Delay and Sum (DAS) beamforming technique, which relies solely on the temporal information of the full matrix capturing dataset while ignoring its spatial information, and the image resolution and contrast achievable with TFM are limited. In this work, a parallel sparse delay multiply and sum (PSDMAS) focusing imaging algorithm based on sparse arrays and parallel computing is proposed to improve contrast resolution and imaging efficiency. A sparse array optimisation method is applied to reduce the amount of data. A ratio of main-lobe width and side-lobe peak was constructed as the fitness function and a genetic algorithm was used to find the optimal solution for the array arrangement. Delay Multiply and Sum (DMAS) was employed to enhance the spatial coherence and suppress the clutter artefacts. Parallel computing strategies were implemented to improve imaging efficiency. To validate the effectiveness of the algorithm, we processed the full matrix data collected from simulations and experiments using PSDMAS, the imaging results of the PSDMAS provided a considerable improvement in Array Performance Indicator (API), and better lateral spatial resolution was also achieved. The computation time of PSDMAS was reduced by 99.9% compared to conventional DMAS.