Near-field, broadband adaptive beamforming for ultrasound imaging
For over fifty years adaptive beamforming (ABF) algorithms have been applied in RADAR and SONAR signal processing. These algorithms reduce the contribution of undesired off-axis signals while maintaining a desired response along a specific look direction. Typically, ABF achieves higher resolution and contrast than conventional beamforming (CBF), at the price of an increased computational load. In this paper we describe a novel ABF designed for medical ultrasound, named the Time-domain Optimized Near-field Estimator, or TONE. We performed a series of simulations using ultrasound data to test the performance of this algorithm and compare it to conventional, data independent, delay and sum beamforming. We also performed experiments using a Philips SONOS 5500. CBF was applied using the default parameters of the Philips scanner, whereas TONE was applied on single-channel, unfocused data with plane wave transmit. TONE images were reconstructed at a sampling of 67μm laterally and 19μm axially. The results obtained for a series of 5 20μm wires in a water tank show a significant improvement in spatial resolution when compared to CBF. We also analyzed the performance of TONE as a function of speed of sound errors and array sparsity, finding TONE robust to both.