Compressed Plane-Wave Compounding for Efficient Imaging on Portable Ultrasound Devices

Sub-Nyquist sampling, also known as compressive sensing (CS), leverages the sparsity of ultrasound signals to reduce the sampling rate required for accurate ultrasound image reconstruction. Such under-sampling can reduce the computational complexity of the reconstruction algorithm while also relaxing on-board memory requirements. This paper demonstrates up to $10 \times$ reduction in total sample count by applying CS algorithms to ultrasound imaging using coherent plane-wave compounding (CPWC), and up to $57 \times$ reduction for single plane waves by combining CS with convolution beamforming. The resulting compression facilitates processing of the acquired samples directly on portable ultrasound devices, thus eliminating the need to transmit the data to a remote cloud for processing. The proposed compressed CPWC imaging approach is suitable for efficient target localization during focused ultrasound (FUS) neuromodulation. A portable ultrasound system for FUS neuromodulation, based on a system-on-chip (SoC) module and equipped with a dual-mode wearable probe, is also presented.