Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU

被引:1
|
作者
Techavipoo, Udomchai [1 ]
Worasawate, Denchai [2 ]
Boonleelakul, Wittawat [2 ]
Keinprasit, Rachaporn [1 ]
Sunpetchniyom, Treepop [1 ]
Sugino, Nobuhiko [3 ]
Thajchayapong, Pairash [1 ]
机构
[1] Natl Elect & Comp Technol Ctr, Pathum Thani 12120, Thailand
[2] Kasetsart Univ, Fac Engn, Dept Elect Engn, Bangkok 10900, Thailand
[3] Tokyo Inst Technol, Dept Informat Proc, Tokyo 1528552, Japan
关键词
array transducer; CUDA; dynamic receive beamforming; graphics processing unit; image reconstruction; ultrasound imaging; REALIZATION; BEAMFORMER; SYSTEM; SIGNAL;
D O I
10.3390/s16121986
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared.
引用
收藏
页码:2 / 17
页数:17
相关论文
共 50 条
  • [1] Ultrasound Beamforming and Image Reconstruction using CPU and GPU
    Boonleelakul, Wittawat
    Techavipoo, Udomchai
    Worasawate, Denchai
    Keinprasit, Rachaporn
    Sunpetchniyom, Treepop
    Sugino, Nobuhiko
    Chayapong, Pairash Thai
    2016 13TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON), 2016,
  • [2] Toward parallel optimal computation of ultrasound computed tomography using GPU
    Xia Sun
    Wang, Shanshan
    Song, Junjie
    Liang Zhou
    Yang Peng
    Ding, Mingyue
    Ming Yuchi
    MEDICAL IMAGING 2018: ULTRASONIC IMAGING AND TOMOGRAPHY, 2018, 10580
  • [3] Rapid computation of sodium bioscales using gpu-accelerated image reconstruction
    Atkinson, Ian C.
    Liu, Geng
    Obeid, Nady
    Thulborn, Keith R.
    Hwu, Wen-mei
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2013, 23 (01) : 29 - 35
  • [4] MR image reconstruction using the GPU
    Schiwietz, Thomas
    Chang, Ti-chiun
    Speier, Peter
    Westermann, Ruediger
    MEDICAL IMAGING 2006: PHYSICS OF MEDICAL IMAGING, PTS 1-3, 2006, 6142
  • [5] GPU/CPU parallel computation of material damage
    Shen, Jie
    Vela, Diego
    Singh, Ankita
    Song, Kexing
    Zhang, Guoshang
    LaFreniere, Bradon
    Chen, Hao
    ENGINEERING WITH COMPUTERS, 2015, 31 (03) : 647 - 660
  • [6] GPU/CPU parallel computation of material damage
    Jie Shen
    Diego Vela
    Ankita Singh
    Kexing Song
    Guoshang Zhang
    Bradon LaFreniere
    Hao Chen
    Engineering with Computers, 2015, 31 : 647 - 660
  • [7] IMAGE INTERPOLATION ON THE CPU AND GPU USING LINE RUN SEQUENCES
    Frommholz, Dirk
    XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II, 2022, 5-2 : 53 - 60
  • [8] A regularized MRI image reconstruction based on Hessian penalty term on CPU/GPU systems
    Piccialli, Francesco
    Cuomo, Salvatore
    De Michele, Pasquale
    2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, 2013, 18 : 2643 - 2646
  • [9] Optimizing Image Reconstruction in SENSE Using GPU
    Sohaib A. Qazi
    Saima Nasir
    Abeera Saeed
    Hammad Omer
    Applied Magnetic Resonance, 2018, 49 : 151 - 164
  • [10] Optimizing Image Reconstruction in SENSE Using GPU
    Qazi, Sohaib A.
    Nasir, Saima
    Saeed, Abeera
    Omer, Hammad
    APPLIED MAGNETIC RESONANCE, 2018, 49 (02) : 151 - 164