计算机应用 ›› 2011, Vol. 31 ›› Issue (03): 856-859.DOI: 10.3724/SP.J.1087.2011.00856

• 典型应用 • 上一篇    下一篇

基于CUDA的彩色超声血流成像

范正娟1,谭朝炜2,刘东权1   

  1. 1. 四川大学 计算机学院,成都610064
    2. 声泰特(成都)科技有限公司,成都610041
  • 收稿日期:2010-08-30 修回日期:2010-10-14 发布日期:2011-03-03 出版日期:2011-03-01
  • 通讯作者: 范正娟
  • 作者简介:范正娟(1987-),女,重庆忠县人,硕士研究生,主要研究方向:医学超声图像处理;谭朝炜(1983-),男,重庆人,硕士,主要研究方向:计算机视觉、可视化、高性能计算;刘东权(1956-),男,美国华盛顿州人,教授,博士生导师,主要研究方向:医学超声图像处理。

Ultrasound color flow imaging based on compute unified device architecture

FAN Zheng-juan1,TAN Chao-wei2,Dong C. LIU1   

  1. 1. College of Computer Science, Sichuan University, Chengdu Sichuan 610064, China
    2. Saset (Chengdu) Incorporation, Chengdu Sichuan 610041, China
  • Received:2010-08-30 Revised:2010-10-14 Online:2011-03-03 Published:2011-03-01
  • Contact: FAN Zheng-juan

摘要: 彩色超声血流成像在医学超声诊断中得到了广泛的运用。对前期所提出的超声血流成像图形处理器(GPU)的处理框架做出了两点改进:在壁滤波器模块并行实现Regression滤波器,替换原来的并行有限冲激响应(FIR)滤波器;在后处理模块中,加入了并行实现的Threshold box滤波器,改善了血流的均匀性。实验结果表明:GPU并行实现的运算效率是中央处理器(CPU)串行实现的16.2倍,帧率可以达到70帧/秒。与传统的FIR滤波器相比,Regression滤波器能够得到更高质量的超声血流图像,并且Threshold box滤波器提高了组织/血流鉴定的精确度。

关键词: 彩色超声血流成像, 有限冲激响应滤波器, Regression 滤波器, Threshold box滤波器, 计算统一设备架构

Abstract: Ultrasound Color Flow Imaging (CFI) is widely used in clinical diagnosis. This paper made two improvements for previous research about Graphics Processing Unit (GPU) framework for CFI: on wall filtering block, the parallel regression filtering was implemented instead of Finite Impulse Response (FIR) filter; on post-processing block, the parallel threshold box filtering was added to improve flow uniformity. The experimental data were acquired from a healthy carotid artery: 88 scan lines, 510 samples along the scan line, and an ensemble size of 16. The experimental results show that, compared with the serial algorithm based on Central Processing Unit (CPU), the computational efficiency of the proposed parallel algorithms based on GPU has been increased by 15.2 times and the frame rate increases up to 70. The color flow image can achieve a high quality by the regression filter instead of FIR filter, and improve the accuracy of tissue/flow detection by threshold box filter.

Key words: ultrasound Color Flow Imaging (CFI), Finite Impulse Response (FIR) filter, Regression filter, Threshold box filter, Compute Unified Device Architecture (CUDA)

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