Real-Time Full-Volume Row-Column Imaging

An implementation of volumetric beamforming for row-column addressed arrays (RCAs) 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 ≥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 CUDA C++, was modified to implement the dual-stage imaging with optimizations. In-vivo rat kidney data was 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 pre-processing, was measured for an NVIDIA GeForce RTX 4090 GPU, and the resulting beamforming rate was 1440 volumes per second, 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 3D imaging can be performed in real time with a setup similar to 2D imaging: Using a single graphics card, one scanner, and 128 transmit/receive channels.