The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
권호 표지
DOI QR코드

DOI QR Code

Image enhancement in ultrasound passive cavitation imaging using centroid and flatness of received channel data

수신 채널 신호의 무게중심과 평탄도를 이용한 초음파 수동 공동 영상의 화질 개선

  • 정목근 (대진대학교 전기 및 전자공학부) ;
  • 권성재 (대진대학교 휴먼IT융합학부) ;
  • 최민주 (제주대학교 의학전문대학원 의공학교실)
  • Received : 2019.05.09
  • Accepted : 2019.06.25
  • Published : 2019.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

Passive cavitation imaging method is used to observe the ultrasonic waves generated when a group of bubbles collapses. A problem with passive cavitation imaging is a low resolution and large side lobe levels. Since ultrasound signals generated by passive cavitation take the form of a pulse, the amplitude distribution of signals received across the receive channels varies depending on the direction of incidence. Both the centroid and flatness were calculated to determine weights at imaging points in order to discriminate between the main and side lobe signals from the signal amplitude distribution of the received channel data and to reduce the side lobe levels. The centroid quantifies how the channel data are distributed across the receive channel, and the flatness measures the variance of the channel data. We applied the centroid weight and the flatness to the passive cavitation image constructed using the delay-and-sum focusing and minimum variance beamforming methods to improve the image quality. Using computer simulation and experiment, we show that the application of weighting in delay-and-sum and minimum variance beamforming reduces side lobe levels.

기포군이 파열하면서 발생하는 초음파를 관찰하기 위하여 수동 공동 영상법을 이용한다. 수동 공동 영상은 낮은 해상도와 큰 부엽이 문제이다. 수동 공동에서 발생하는 초음파 신호는 펄스 형태를 가지므로, 수신 어레이에 수신된 신호는 입사 방향에 따라서 트랜스듀서 배열 소자에 나타나는 신호의 크기 분포가 달라진다. 영상점에서 수신된 채널 데이터 신호의 크기 분포로부터 주엽과 부엽 신호의 유무를 판단하고 부엽을 줄이기 위하여 무게중심과 평탄도를 계산하여 영상점에서 가중값을 정의하였다. 무게중심은 수신 채널에서 신호의 분포가 집중된 위치를 수치화하며 평탄도는 채널 신호의 분산을 측정한다. 지연 후 더해주는 집속 방식과 최소 분산 빔포밍을 사용하여 구현된 수동 공동 영상에서 무게중심과 평탄도를 이용한 가중값을 적용하여 영상의 화질 개선에 적용하였다. 컴퓨터 시뮬레이션과 실험에서 지연 후 더해주는 방법과 최소 분산 빔포밍 방법에 가중값을 적용하여 영상에서 부엽이 줄어듦을 확인하였다. 고출력 초음파를 이용한 수조 실험에서도 부엽이 나타나는 영역이 줄어들어 수동 공동의 변별력이 증가함을 확인하였다.

Keywords

GOHHBH_2019_v38n4_450_f0001.png 이미지

Fig. 1. Architecture of delay-and-sum beamforming system using array transducer.

GOHHBH_2019_v38n4_450_f0002.png 이미지

Fig. 2. Waveforms of echoes across transducer array: (a) from imaging p oint and ( b) not f rom imaging point.

GOHHBH_2019_v38n4_450_f0003.png 이미지

Fig. 3. Weighting values as a function of centroid in a 64 channel imaging system: triangular weight (solid) and weight corresponding to the fourth power of the Hamming window (dashed).

GOHHBH_2019_v38n4_450_f0004.png 이미지

Fig. 4. Temporal evolution of channel RF waveform due to cavitation.

GOHHBH_2019_v38n4_450_f0005.png 이미지

Fig. 5. Images of a point like bubble obtained using (a) DAS without compression and (b) MVB with 40 dB logarithmic compression.

GOHHBH_2019_v38n4_450_f0006.png 이미지

Fig. 6. 2-D maps of (a) centroid weighting, (b) flatness, and (c) multiplication of centroid weighting and flatness.

GOHHBH_2019_v38n4_450_f0007.png 이미지

Fig. 7. Images obtained using (a) weighted DAS and (b) weighted MVB, both with a 40 dB log compression.

GOHHBH_2019_v38n4_450_f0008.png 이미지

Fig. 8. Lateral field responses: DAS (solid), weighted DAS (dotted), MVB (dashed), and weighted MVB (dash-dotted).

GOHHBH_2019_v38n4_450_f0009.png 이미지

Fig. 9. Axial field responses: DAS (solid), weighted DAS (dotted), MVB (dashed), and weighted MVB (dash-dotted).

GOHHBH_2019_v38n4_450_f0010.png 이미지

Fig. 10. Experimental setup.

GOHHBH_2019_v38n4_450_f0011.png 이미지

Fig. 11. Experimental setup: (a) relative placement of shock wave generation and imaging probes for alignment and (b) B-mode image of cavitation due to shock wave.

GOHHBH_2019_v38n4_450_f0012.png 이미지

Fig. 13. (a) RF echo from single bubble collapse, (b) DAS image, (c) MVB image, (d) RF echo from two adjacent bubble collapse, (e) DAS image, and (f) MVB image.

GOHHBH_2019_v38n4_450_f0013.png 이미지

Fig. 12. Part of 64 channels of RF data.

GOHHBH_2019_v38n4_450_f0014.png 이미지

Fig. 15. B-mode images of (a) weighted single bubble collapse using DAS, (b) weighted single bubble collapse using MVB, (c) weighted two bubble collapse using DAS, and (d) weighted two bubble collapse using MVB.

GOHHBH_2019_v38n4_450_f0015.png 이미지

Fig. 14. Plots of (a) centroid weighting from single bubble collapse data, (b) uniformity of single bubble collapse image, (c) weighting factor obtained by multiplying together centroid weighting and flatness of single bubble collapse image, (d) centroid weighting from two adjacent bubble collapse data, (e) flatness of two bubble collapse image, and (f) weighting factor obtained by multiplying together centroid weighting and flatness of two bubble collapse image.

References

  1. V. A. Salgaonkar, S. Datta, C. K. Holland, and T. D. Mast, "Passive cavitation imaging with ultrasound arrays," J. Acoust. Soc. Am. 126, 3071-3083 (2009). https://doi.org/10.1121/1.3238260
  2. P. Boulos, F. Varray, A. Poizat, J. C. Bera, and C. Cachard, "Passive cavitation imaging using an open ultrasonic system and time reversal reconstruction," Proc. 22nd French Mechanics Congress (2015).
  3. C. Coviello, R. J. Kozick, J. J. Choi, M. Gyöngy, J. Collin, C. Jensen, P. P. Smith, and C. C. Coussios, "Passive acoustic mapping using optimal beamforming for real-time monitoring of ultrasound therapy," Proc. Meetings on Acoustics, 1-7 (2013).
  4. P. Boulos, F. Varray, A. Poizat, M. A. Kalkhoran, B. Gilles, J. C. Bera, and C. Cachard, "Passive cavitation imaging using different advanced beamforming methods," Proc. IEEE Ultrasonics Symposium (2016).
  5. J. H. Song, S. Cochran, P. Prentice, G. McLeod, and G. Corner, "Role of periodic shock waves in passive acoustic mapping of cavitation," Proc. IEEE Ultrasonics Symposium (2016).
  6. M. Gyongy and C. C. Coussios, "Passive spatial mapping of inertial cavitation during HIFU exposure," IEEE Trans. Biomedical Engineering, 57, 48-56 (2010). https://doi.org/10.1109/TBME.2009.2026907
  7. J. A. Jensen and N. B. Svendsen, "Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers," IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., 39, 262-267 (1992). https://doi.org/10.1109/58.139123
  8. D. A. Guenther and W. F. Walker, "Optimal apodization design for medical ultrasound using constrained least squares. Part I: Theory," IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., 54, 332-342 (2007). https://doi.org/10.1109/TUFFC.2007.247
  9. D. A. Guenther and W. F. Walker, "Optimal apodization design for medical ultrasound using constrained least squares. Part II: Simulation results," IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., 54, 343-358 (2007). https://doi.org/10.1109/TUFFC.2007.248
  10. I. K. Holfort, F. Gran, and J. A. Jensen, "Broadband minimum variance beamforming for ultrasound imaging," IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., 56, 314-325 (2009). https://doi.org/10.1109/TUFFC.2009.1040
  11. K. Kim, S. Park, J. Kim, S. B. Park, and M. H. Bae, "A fast minimum variance beamforming method using principal component analysis," IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., 61, 930-945 (2014). https://doi.org/10.1109/TUFFC.2014.2989