Earticle

초록

영어

The ability to detect and assess information of blood flow in color Doppler imaging (CDI) has played one of the most important roles in a modern ultrasound imaging system. However, since CDI requires large amount of data and computations, it has been mainly implemented on custom-designed hardware. Recent trend of programmable approach offers the advantages of flexibility and quick implementation. Specifically, general-purpose GPUs have been emerged as excellent accelerators across a wide range of applications. For best exploiting outstanding computational power, high memory bandwidth and SIMD architecture of a GPU, this paper explores the design space of CDI on GPU architecture platform and presents a high performance implementation of CDI on the GPU platform using CUDA API. The performance analysis shows our GPU-based CDI can achieve a frame rate of 152 for 800 range samples and 200 scan lines with an ensemble size of 12. Speedup of 19.8x can be obtained when compared with that on a CPU platform.

목차

Abstract
 1. Introduction
 2. Preliminaries
  2.1. Ultrasound Imaging
  2.2. Color Doppler Imaging
  2.3. GPU Architecture and Programming Model
 3. GPU-based Color Doppler Imaging Implementation
  3.1. Implementation Platform and parameters setting
  3.2. Implementation Method and Performance Analysis
 4. Conclusion
 References

키워드

저자

• Thi-Yen Phuong [ Dept. of Computer Science, Hallym University ]
• Jeong-Gun Lee [ Dept. of Computer Science, Hallym University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605