Random aperture optimization for SRAC in high frame rate volume imaging

High frame-rate volume imaging (HFVI) has become a mayor area of research in the last decade. Unfortunately, HFVI usually requires ultrasound systems with a large channel count. Sparse Random Aperture Compounding (SRAC) is a technique that uses random apertures to reduce the number of channels necessary. This approach compounds images from complementary random apertures to balance image quality and frame rate. In the current work we used a Monte Carlo method to optimize random apertures to improve image quality without sacrificing temporal resolution. We also evaluated if complementarity of random apertures plays a significant role in the image quality. A Vantage 256 system equipped with a 1024 MUX UTA and a 3 MHz matrix probe (1024 elements) was used for this study. A series of 1250 groups of complementary random apertures were created (a total of 5000 apertures). A single diverging wave acquisition was used for imaging a phantom with a string at a depth of 53 mm. The apertures were sorted using the Main-lobe to Side-lo Ratio (MLSLR) from best to worst. The optimization process showed an improvement in the image quality of 9.5 dB in MLSLR between the best and worst apertures. SRAC of complementary apertures show an increase in the MLSR from 1 SRAC to 4 SRAC of 2.5 dB, while for non-complementary apertures this value was 1 dB. While previous studies have demonstrated the advantage of using SRAC for HFIV, this work revealed the importance of aperture optimization and complementarity as well as the significance of selecting the proper apertures for a given application.