Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Estimation of Medical Ultrasound Attenuation using Adaptive Bandpass Filters

적응 대역필터를 이용한 의료 초음파 감쇠 예측

  • Heo, Seo-Weon (Department of Electronic, Information & Communication Engineering, Hongik University) ;
  • Yi, Joon-Hwan (Department of Electrical Engineering, Kwangwoon University) ;
  • Kim, Hyung-Suk (Department of Electrical Engineering, Kwangwoon University)
  • 허서원 (홍익대학교 전자정보통신공학과) ;
  • 이준환 (광운대학교 전기공학과) ;
  • 김형석 (광운대학교 전기공학과)
  • Received : 2010.03.04
  • Published : 2010.09.25
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Abstract

Attenuation coefficients of medical ultrasound not only reflect the pathological information of tissues scanned but also provide the quantitative information to compensate the decay of backscattered signals for other medical ultrasound parameters. Based on the frequency-selective attenuation property of human tissues, attenuation estimation methods in spectral domain have difficulties for real-time implementation due to the complexicity while estimation methods in time domain do not achieve the compensation for the diffraction effect effectively. In this paper, we propose the modified VSA method, which compensates the diffraction with reference phantom in time domain, using adaptive bandpass filters with decreasing center frequencies along depths. The adaptive bandpass filtering technique minimizes the distortion of relative echogenicity of wideband transmit pulses and maximizes the signal-to-noise ratio due to the random scattering, especially at deeper depths. Since the filtering center frequencies change according to the accumulated attenuation, the proposed algorithm improves estimation accuracy and precision comparing to the fixed filtering method. Computer simulation and experimental results using tissue-mimicking phantoms demonstrate that the distortion of relative echogenicity is decreased at deeper depths, and the accuracy of attenuation estimation is improved by 5.1% and the standard deviation is decreased by 46.9% for the entire scan depth.

의료 초음파 신호의 인체내 감쇠지수는 검사대상 조직의 병리학적 특성을 반영할 뿐 아니라 다른 여러 의료 초음파 지수들의 정확한 예측을 위해 선행하여 측정해야 하는 중요한 정량적 정보 중 하나이다. 그러나 초음파 감쇠지수의 주파수 선택적 감쇠특성을 이용한 주파수 영역에서의 정량적 감쇠지수 예측 방법은 계산량이 많아 실시간 적용에 많은 어려움이 있고, 상대적으로 계산량이 적은 시간 영역의 감쇠지수 예측 방법은 전송 펄스의 회절효과를 잘 보상하지 못하는 단점이 있다. 표준 반향신호를 이용하여 전송 펄스의 회절효과를 보상하는 시간 영역의 예측 알고리듬인 VSA(Video Signal Analysis) 방법은 광대역 펄스를 이용하는 경우, 원거리에서 반향된 신호의 왜곡이 발생하여 예측 정확도가 저하되는 단점이 있다. 본 논문에서는 그 단점을 해결하기 위해 적응 대역필터를 이용한 초음파 감쇠지수 예측 알고리듬을 제안한다. 제안된 방식은 반향 경로를 따라 누적된 신호 감쇠를 고려하여 적응 대역필터의 중심 주파수를 이동시킴으로써, 기존의 고정 대역필터를 사용하는 방법보다 예측 정확도와 정밀도를 높인다. 인체 조직의 초음파 반향특성을 모방한 컴퓨터 모의실험과 실제 TM(tissue-mimicking) phantom을 이용한 실험에서, 광대역 전송 펄스를 사용하는 경우보다 반향 깊이에 따른 상대적 echogenicity의 왜곡이 크게 감소하여 평균적으로 예측 감쇠지수의 정확도가 5.1% 향상되었고, 예측 편차도 기존의 방법에 비해 46.9% 감소되었다.

Keywords

References

  1. K. A. Dines and A. C. Kak, "Ultrasonic attenuation tomography of soft tissues," Ultrason. Imaging, vol. 1 ,pp. 16-33, 1979. https://doi.org/10.1177/016173467900100102
  2. G. Berger, P. Laugier, M. Fink, and J. Perrin, "Optimal precision in ultrasound attenuation estimation and application to the detection of Duchenne muscular dystrophy carriers," Ultrason. Imaging, vol. 9, pp. 1-17, 1987. https://doi.org/10.1177/016173468700900101
  3. P. A. Narayana and J. Ophir, "On the frequency dependence of attenuation in normal and fatty liver," IEEE Trans. Sonics Ultrason., vol. 30, no. 6, pp. 379-383, 1983. https://doi.org/10.1109/T-SU.1983.31444
  4. B. J. Oosterveld, J. M. Thijssen, P. C. Hartman, R. L. Romijn, and G. J. Rosenbusch, "Ultrasound attenuation and texture analysis of diffuse liver disease: methods and preliminary results," Phys. Med. Biol., vol. 36, no. 8, pp. 1039-1064, 1991. https://doi.org/10.1088/0031-9155/36/8/002
  5. G. Berger, P. Laugier, J. C. Thalabard, and J. Perrin, "Global breast attenuation : control group and benign breast diseases," Ultrason. Imaging, vol. 12, no. 1, pp. 47-57, 1990. https://doi.org/10.1177/016173469001200104
  6. S. W. Flax, N. J. Pelc, G. H. Glover, F. D. Gutmann, and M. McLachlan, "Spectral characterization and attenuation measurements in ultrasound," Ultrason. Imaging, vol. 5, no. 2, pp. 95-116, 1983.
  7. H. S. Jang, T. K. Song, and S. B. Park, "Ultrasound attenuation estimation in soft tissue using the entropy difference of pulsed echoes between two adjacent envelope segments," Ultrason. Imaging, vol. 10, no. 4, pp. 248-264, 1988.
  8. M. Fink, F. Hottier, and J. F. Cardoso, "Ultrasonic signal processing for in vivo attenuation measurement: short time Fourier analysis," Ultrason. Imaging, vol. 5, no. 2, pp. 117-135, 1983.
  9. H. Kim and T. Varghese, "Attenuation estimation using spectral cross-correlation," IEEE Trans. Ultrason. Ferroelec. and Freq. Control, vol. 54, no. 3, pp. 510-519, 2007. https://doi.org/10.1109/TUFFC.2007.274
  10. L. X. Yao, J. A. Zagzebski, and E. L. Madsen, "Backscatter coefficient measurements using a reference phantom to extract depth-dependent instrumentation factors," Ultrason. Imaging, vol. 12, no. 1, pp. 58-70, 1990. https://doi.org/10.1177/016173469001200105
  11. S. W. Flax, N. J. Pelc, G. H. Glover, F. D. Gutmann, and M. McLachlan, "Spectral characterization and attenuation measurements in ultrasound," Ultrason. Imaging, vol. 5, no. 2, pp. 95-116, 1983. https://doi.org/10.1177/016173468300500201
  12. P. He and J. F. Greenleaf, "Application of stochastic-analysis to ultrasonic echoes - estimation of attenuation and tissue heterogeneity from peaks of echo envelope," Journal o f Acoustical Society of America, vol. 79, no. 2, pp. 526-534, 1986. https://doi.org/10.1121/1.393540
  13. H. S. Jang, T. K. Song, and S. B. Park, "Ultrasound attenuation estimation in soft tissue using the entropy difference of pulsed echoes between two adjacent envelope segments," Ultrason. Imaging, vol. 10, no. 4, pp. 248-264, 1988. https://doi.org/10.1177/016173468801000402
  14. B. S. Knipp, J. A. Zagzebski, T. A. Wilson, F. Dong, E. L. Madsen, "Attenuation and backscatter estimation using video signal analysis applied to B-mode images," Ultrason. Imaging, vol. 19, no. 3, pp. 221-233, 1997. https://doi.org/10.1177/016173469701900305
  15. H. Kim, J. A. Zagzebski, and T. Varghese, "Estimation of ultrasound attenuation from broadband echo-signals using bandpass filtering," IEEE Trans. Ultrason. Ferroelec. and Freq. Control, vol. 55, no. 5, pp. 1153-1159, 2008. https://doi.org/10.1109/TUFFC.2008.768
  16. L. S. Wilson, D. E. Robinson, and B. D. Doust, "Frequency domain processing for ultrasonic attenuation measurement in liver," Ultrason. Imaging, vol. 6, pp. 278-292, 1984. https://doi.org/10.1177/016173468400600303
  17. C. Kasai, K. Namekawa, A. Koyano, and R. Omoto, "Real-time two-dimensional blood flow imaging using an autocorrelation technique," IEEE Trans. Sonics and Ultrasonics, vol. 32, no. 3, pp. 458-464, 1985. https://doi.org/10.1109/T-SU.1985.31615
  18. Y. Li and J. A. Zagzebski, "A frequency domain model for generating B-mode images with array transducers," IEEE Trans. Ultrason. Ferroelec. and Freq. Control, vol. 46, no. 3, pp. 690-699, 1999. https://doi.org/10.1109/58.764855