The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
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Improvements of Pulse Doppler Gap Filling Algorithms for Portable Medical Ultrasound Imaging System

휴대용 초음파진단기를 위한 펄스 도플러 갭 필링 알고리즘의 개선

  • Bae, MooHo (Department of Electronics Engineering, Hallym University) ;
  • An, Hyung-Jun (Department of Electronics Engineering, Hallym University)
  • 배무호 (한림대학교 정보전자공학대학 전자공학과) ;
  • 안형준 (한림대학교 정보전자공학대학 전자공학과)
  • Received : 2012.07.13
  • Accepted : 2012.10.05
  • Published : 2012.11.30
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Abstract

In this paper, we studied on Doppler gap-filling algorithms suitable for a portable or low-cost medical ultrasound imaging system, and as a result, found out algorithms based on mirroring or autoregressive model. Moreover, controlling the computational demand in the proper range, we improved the performances of these algorithms by solving their problems. Effectiveness of these modified algorithms is verified by computer simulations and experiments which used artificially generated Doppler signals and Doppler data acquired from human body through an actual ultrasound system.

이 논문에서는 휴대용, 또는 저가형 초음파진단기에 비교적 고급 기능인 도플러 갭 필링 모드를 적용하고자할 때 적합한 알고리즘들을 찾아보았고, 그 결과 미러링 기반, 또는 자기회귀 모델 기반의 알고리즘들을 찾을 수 있었다. 또, 계산량이 지나치게 많아지지 않는 범위 내에서, 그러한 알고리즘들의 성능의 문제점을 보완하여 더욱 개선시켰다. 수정된 알고리즘들은 인공적으로 발생시킨 도플러 신호 및 실제 초음파장비를 써서 인체로부터 획득한 도플러 데이터를 써서 시뮬레이션 및 실험을 함으로써 유효성을 확인하였다.

Keywords

References

  1. J. A. Zagzebski, Essentials of ultrasound physics, Mosby Inc. Maryland Heights, 1996.
  2. K. Kristoffersen and B. A. J. Angelsen, "A time-shared ultrasound Doppler measurement and 2-D imaging system," IEEE Trans. Biomed. Eng., vol. 35, no. 5, pp. 285-295, May 1988. https://doi.org/10.1109/10.1383
  3. H. Klebaek, J. A. Jensen, and L. K. Hansen, "Neural network for sonogram gap filling," Proc. IEEE Ultrason. Symp., pp. 1553-1556, 1995.
  4. W. Wilkening, B. Brendel, and H. Ermert, "Fast, extended velocity range flow imaging based on nonuniform sampling using adaptive wall filtering and cross correlation," Proc. IEEE Ultrason. Symp., pp. 1457-1460, 2002.
  5. J. A. Jensen, "Spectral velocity estimation using the autocorrelation function and sparse data sequences," Proc. IEEE Ultrason. Symp., pp. 141-145, 2005.
  6. S. K. Mollenbach. and J. A. Jensen, "Duplex scanning using sparse data sequences," Proc. IEEE Ultrason. Symp., pp. 5-8, 2008
  7. M. Izumi, "Ultrasonic wave Doppler diagnosing apparatus," US Patent no. 5,891,036, Apr. 1999.
  8. Y. Zhang and X. Li, "Method and apparatus for fFilling Doppler signal gaps in ultrasound diagnostic imaging," US Patent Application Publication, no. US2009/0012398 A1, Jan. 8, 2009.
  9. J. S. Wang, "Aparatus and method for estimating missing Doppler signals and spectra," US Patent no. 5,642,732, Jul. 1997
  10. Y. M. Kim and S. B. Park, "Modeling of Doppler signal considering the sample volume and field distribution," Ultrason. Imag., vol. 11, pp. 175-196, 1989. https://doi.org/10.1016/0161-7346(89)90073-4
  11. A. C. H. Yu, A. H. Steinman, and R. S. C. Cobbold, "Transit-time broadening in pulsed Doppler ultrasound: A generalized amplitude modulation model," IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 53, no. 3, pp. 530-541, Mar. 2006. https://doi.org/10.1109/TUFFC.2006.1610561
  12. A. J. E. M. Janssen, R. N. J. Veldus, and L. B. Vries, "Adaptive interpolation of discrete-time signals that can be modeled as autoregressive process," IEEE Trans. Acoust. Speech Signal Processing, vol. ASSP-34, no. 2, pp. 317-330, April 1986.
  13. S. de Waele and P. M. T. Broersen, "The Burg algorithm for segments," IEEE Trans. Signal Processing, vol. 48, no. 10, pp. 2876-2880, Oct. 2000. https://doi.org/10.1109/78.869039
  14. E. S. Chornoboy, "Initialization for improved IIR filter performance," IEEE Trans. Signal Processing, vol. 40, no. 3, pp. 543-550, Mar. 1992. https://doi.org/10.1109/78.120797
  15. M. H. Hayes, Statistical digital signal processing and modeling, John Wiley & sons, Inc., 1996.