arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2208.03429eess.SP

基于单片FPGA的可扩展超快超声波束形成器的高层次综合设计

High-level synthesis design of scalable ultrafast ultrasound beamformer with single FPGA

Zhengchang Kou, Qi You, Jihun Kim, Zhijie Dong, Matthew R. Lowerison, Nathiya V. Chandra Sekaran, Daniel A. Llano, Pengfei Song, Michael L. Oelze

阅读 PDF
arXiv 页面 ↗HTML 原文 ↗

AI总结：

本文提出在单片FPGA上利用高层次综合实现可扩展超快平面波成像波束形成器，通过延迟压缩、延迟复用、通道数据向量化和固定求和网络，达到4.83 G样本/秒的波束形成速率，并验证了与软件波束形成器相当的成像质量。

摘要：

超快超声成像对于超声定位显微镜（ULM）和功能超声（fUS）等先进超声成像技术至关重要。当前的超快超声成像面临与射频（RF）信号相关的超高数据带宽挑战，以及计算量巨大的波束形成过程所带来的延迟问题。因此，基于CPU或GPU的现有软件波束形成器难以实现连续的超快数据采集和波束形成。为应对这些挑战，本文提出了一种新方法，利用高层次综合在单片现场可编程门阵列（FPGA）上实现专门用于超快平面波成像（PWI）的超快超声波束形成器。通过在单片FPGA上并行化实现波束形成器，具体包括：1）利用延迟压缩技术减小延迟剖面尺寸，从而支持运行时从外部存储器加载预计算延迟剖面以及延迟复用；2）通过延迟复用实现通道数据读取的向量化；3）使用固定求和网络以减少逻辑资源消耗。与现有FPGA波束形成器相比，本文方法具有两个独特优势：1）高可扩展性，通过使用Xilinx高层次综合作为开发工具，能够快速适应不同的FPGA资源和波束形成速度需求；2）采用单片FPGA而非多片FPGA完成波束形成，实现了紧凑的外形尺寸设计。采用该方法，以输入原始RF样本计，实现了4.83 G样本/秒的可持续平均波束形成速率。在Verasonics Vantage系统上，将所提波束形成器的成像质量与软件波束形成器在体模成像和小鼠脑部在体成像中进行了对比。

英文摘要：

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the ultrahigh data bandwidth associated with the radio frequency (RF) signal, and by the latency of the computationally expensive beamforming process. As such, continuous ultrafast data acquisition and beamforming remain elusive with existing software beamformers based on CPUs or GPUs. To address these challenges, the proposed work introduces a novel method of implementing an ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging (PWI) on a field programmable gate array (FPGA) by using high-level synthesis. A parallelized implementation of the beamformer on a single FPGA was proposed by 1) utilizing a delay compression technique to reduce the delay profile size, which enables both run-time pre-calculated delay profile loading from external memory and delay reuse 2) vectorizing channel data fetching which is enabled by delay reuse, and 3) using fixed summing networks to reduce consumption of logic resources. Our proposed method presents two unique advantages over current FPGA beamformers: 1) high scalability that allows fast adaptation to different FPGA resources and beamforming speed demands by using Xilinx High-Level Synthesis as the development tool, and 2) allow a compact form factor design by using a single FPGA to complete the beamforming instead of multiple FPGAs. With the proposed method, a sustainable average beamforming rate of 4.83 G samples/second in terms of input raw RF sample was achieved. The resulting image quality of the proposed beamformer was compared with the software beamformer on the Verasonics Vantage system for both phantom imaging and in vivo imaging of a mouse brain.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

↑