首页> 外文OA文献 >GPU-based beamformer: Fast realization of plane wave compounding and synthetic aperture imaging
【2h】

GPU-based beamformer: Fast realization of plane wave compounding and synthetic aperture imaging

机译:基于GpU的波束形成器:快速实现平面波复合和合成孔径成像

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Although they show potential to improve ultrasound image quality, plane wave (PW) compounding and synthetic aperture (SA) imaging are computationally demanding and are known to be challenging to implement in real-time. In this work, we have developed a novel beamformer architecture with the real-time parallel processing capacity needed to enable fast realization of PW compounding and SA imaging. The beamformer hardware comprises an array of graphics processing units (GPUs) that are hosted within the same computer workstation. Their parallel computational resources are controlled by a pixel-based software processor that includes the operations of analytic signal conversion, delay-and-sum beamforming, and recursive compounding as required to generate images from the channel-domain data samples acquired using PW compounding and SA imaging principles. When using two GTX-480 GPUs for beamforming and one GTX-470 GPU for recursive compounding, the beamformer can compute compounded 512 × 255 pixel PW and SA images at throughputs of over 4700 fps and 3000 fps, respectively, for imaging depths of 5 cm and 15 cm (32 receive channels, 40 MHz sampling rate). Its processing capacity can be further increased if additional GPUs or more advanced models of GPU are used. © 2011 IEEE.
机译:尽管它们显示出改善超声图像质量的潜力,但是平面波(PW)合成和合成孔径(SA)成像在计算上要求很高,并且已知难以实时实现。在这项工作中,我们开发了一种新颖的波束形成器架构,该架构具有能够快速实现PW复合和SA成像所需的实时并行处理能力。波束形成器硬件包括托管在同一计算机工作站内的一系列图形处理单元(GPU)。它们的并行计算资源由基于像素的软件处理器控制,该处理器包括分析信号转换,延迟和求和波束成形以及根据需要从使用PW混合和SA获取的通道域数据样本生成图像的递归复合操作成像原理。当使用两个GTX-480 GPU进行波束成形和一个GTX-470 GPU进行递归复合时,对于5厘米的成像深度,波束成形器可以分别以超过4700 fps和3000 fps的吞吐量计算复合的512×255像素PW和SA图像。和15厘米(32个接收通道,40 MHz采样率)。如果使用其他GPU或更高级的GPU模型,则可以进一步提高其处理能力。 ©2011 IEEE。

著录项

  • 作者

    Yu ACH; Tsang IKH; Yiu BYS;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号