Real-Time Full-Volume Row-Column Imaging

Abstract

An implementation of volumetric beamforming for row-column addressed (RCA) arrays is proposed, with optimizations for graphics processing units (GPUs). It is hypothesized that entire volumes can imaged in real-time by a consumer-class GPU at an emission rate $\geq 12$ kHz. A separable beamforming algorithm was used to reduce the number of calculations with a negligible impact on the image quality. Here, a single image was beamformed for each emission and then extrapolated to reproduce the volume, which resulted in $65\times $ fewer calculations per volume. Reusing computations and samples among adjacent pixels and frames reduced the amount of overhead and load instructions, increasing performance. A GPU beamformer, written in compute unified device architecture (CUDA) C++, was modified to implement the dual-stage imaging with optimizations. In vivo rat kidney data were acquired using a 6-MHz Vermon 128 + 128 RCA probe and a Verasonics Vantage 256 scanner. The acquisition used 96 defocused emissions at a 12-kHz rate for a volume acquisition rate of 125 Hz. Processing time, including all preprocessing, was measured for an NVIDIA GeForce RTX 4090 GPU, and the resulting beamforming rate was 1440 volumes/s, greatly exceeding the real-time rate. Based on the GPU’s floating-point throughput, this corresponds to 22% of the theoretically achievable rate. High efficiency was also shown for an RTX 2080 Ti and RTX 3090, both achieving real-time imaging. This shows that 3-D imaging can be performed in real-time with a setup similar to 2-D imaging: using a single graphics card, one scanner, and 128 transmit/receive channels.