计算机应用 ›› 2011, Vol. 31 ›› Issue (10): 2760-2763.DOI: 10.3724/SP.J.1087.2011.02760

• 图形图像技术 • 上一篇    下一篇

CUDA平台下的实时超声扫描转换

王伟民,王合闯,王华军   

  1. 成都理工大学 信息科学与技术学院, 成都 610059
  • 收稿日期:2011-04-14 修回日期:2011-06-22 发布日期:2011-10-11 出版日期:2011-10-01
  • 通讯作者: 王伟民
  • 作者简介:王伟民(1987-),男,陕西渭南人,硕士研究生,主要研究方向:医学超声图像处理、并行计算;王合闯(1975-),男,河南濮阳人,博士研究生,主要研究方向:并行计算;王华军(1964-),男,四川眉山人,教授,博士生导师,博士,主要研究方向:现代信息通信。

Real-time scan conversion for ultrasound based on CUDA

WANG Wei-min, WANG He-chuang, WANG Hua-jun   

  1. College of Computer Science and Technology, Chengdu University of Technology, Chengdu Sichuan 610059, China
  • Received:2011-04-14 Revised:2011-06-22 Online:2011-10-11 Published:2011-10-01

摘要: 为了克服传统医学超声扫描转换不能实时的缺陷,实时超声扫描转换算法利用计算统一设备架构(CUDA)技术,通过分配最优的线程结构、合理规划中央处理器(CPU)和图形处理器(GPU)之间的数据传输方式和计算任务的划分,提高了算法的吞吐量,满足了实时性。传统CPU算法和3种GPU算法的实验结果对比显示,GPU处理3121×936大小的图片,帧速率可达746fps,并行算法加速比可达300以上。

关键词: 扇形扫描转换, 插值, 计算统一设备架构, 图形处理器, 并行计算

Abstract: Scan conversion is one of the most important and widely-used technologies in medical ultrasound imaging. Unfortunately, traditional scan conversion algorithm needs intensive computation, which becomes one of the performance bottlenecks of the ultrasound system. In order to overcome this shortcoming, three parallel algorithms called real-time scan conversion for ultrasound based on Compute Unified Device Architecture (CUDA) were proposed. Through assigning the best structure of threads, rationally arranging data transmission between Central Processing Unit (CPU) and Graphic Processing Unit (GPU), and dividing computing tasks, throughput of the algorithm was increased and real-time requirement was met. Finally, this paper compared the three types of real-time scan conversion algorithms on CUDA to traditional method. This paper gets a frame rate of about more than 746fps with the picture size of 3121×936, which is about 300 times faster than the CPU implementation.

Key words: sector scan conversion, interpolation, Computing Unified Device Architecture (CUDA), Graphic Processing Unit (GPU), parallel computing

中图分类号: