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State-Based Gauss-Seidel Framework for Real-time 2D Ultrasound Image Sequence Denoising on GPUs

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJMUE) 바로가기
  • 간행물
    International Journal of Multimedia and Ubiquitous Engineering SCOPUS 바로가기
  • 통권
    Vol.9 No.1 (2014.01)바로가기
  • 페이지
    pp.29-48
  • 저자
    Banpot Dolwithayakul, Chantana Chantrapornchai, Noppadol Chumchob
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A217573

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원문정보

초록

영어
The ultrasound image sequences are not only majorly contaminated by multiplicative noises but they are also usually contaminated with additive noises. As in the past few decades, there were some works, which had focused on removing the noises from ultrasound images, such as in the JY model [1] and in the variational model, which were able to remove both types of noises. However, denoising these noises from the ultrasound image sequence is a time-consuming process that occurred from using fixed-point iterative method. From our investigation, the most time-consuming process part of the denoising process is the Gauss-Seidel. By parallelizing these processes with modern multi-core and many-core processor, the denoising ultrasound image in real-time is possible. In this study, we propose the modified strategy from [2] for managing threads and propose the modified state-based Gauss-Seidel method from [16] for GPUs. Our proposed model can retain the frame order, and get the satisfactory frame rate (about 23.33 fps). The proposed strategy boosts the speedup of the frame denoising to 13.80 times compare to the sequential computation.

목차

Abstract
 1. Introduction
 2. Backgrounds
  2.1. New Variational Model Noise Removal Algorithm
  2.2. Compute Unified Device Architecture (CUDA)
  2.3. Sliding Window Gauss-Seidel
  2.4. State-based Gauss-Seidel
 3. Proposed Strategy
  3.1. Investigation of time used in frame denoising.
  3.2. Modification for State-based Gauss-Seidel for GPU
  3.3. Thread Management Strategy
 4. Experiment Results
  4.1. Denoising Model Validation
  4.2. Performance Results
  4.3. Denoised Image sequence Quality
 5. Conclusion and Future Work
 Acknowledgements
 References

키워드

Real-time image sequence denoising; Parallel computing; OpenMP; Graphic Processing Units (GPUs); multi-core; CUDA; Image processing; Ultrasound image sequence

저자

  • Banpot Dolwithayakul [ Department of Computing, Faculty of Science, Silpakorn University, Thailand ]
  • Chantana Chantrapornchai [ Department of Computer Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand and Department of Computing, Faculty of Science, Silpakorn University, Thailand ]
  • Noppadol Chumchob [ Department of Mathematics, Faculty of Science, Silpakorn University and Centre of Excellence in Mathematics CHE, Si Ayudthaya Rd., Bangkok, Thailand ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Multimedia and Ubiquitous Engineering
  • 간기
    월간
  • pISSN
    1975-0080
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.9 No.1

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