Journal of Real-Time Image Processing

, Volume 16, Issue 2, pp 505–521 | Cite as

A multi-FPGA architecture-based real-time TFM ultrasound imaging

  • Mickael NjikiEmail author
  • Abdelhafid ElouardiEmail author
  • Samir Bouaziz
  • Olivier Casula
  • Olivier Roy
Original Research Paper


Real-time imaging, using ultrasound techniques, is a complex task in non-destructive evaluation. In this context, fast and precise control systems require design of specialized parallel architectures. Total focusing method (TFM) for ultrasound imaging has many advantages in terms of flexibility and accuracy in comparison to traditional imaging techniques. However, one major drawback is the high number of data acquisitions and computing requirements for this imaging technique. Due to those constraints, the TFM algorithm was earlier classified in the field of post-processing tasks. This paper describes a multi-FPGA architecture for real-time TFM imaging using the full matrix capture (FMC). In the acquisition process, data are acquired using a phased array and processed with synthetic focusing techniques such as the TFM algorithm. The FMC-TFM architecture consists of a set of interconnected FPGAs integrated on an embedded system. Initially, this imaging system was dedicated to data acquisition using a phased array. The algorithm was reviewed and partitioned to parallelize processing tasks on FPGAs. The architecture was entirely described using VHDL language, synthesized and implemented on a V5FX70T Xilinx FPGA for the control and high-level processing tasks and four V5SX95T Xilinx FPGAs for the acquisition and low-level processing tasks. The designed architecture performs real-time FMC-TFM imaging with a good characterization of defects.


Non-destructive evaluation Phased arrays TFM Real-time imaging FPGA architecture Hardware software co-design 



This work has been supported by the French institute “Laboratoire d’Intégration de Systèmes et des Technologies” (LIST) from the “Commissariat à l’Energie Atomique” (CEA) in partnership with the M2M-NDT company.


  1. 1.
    Von Ramm, O.T., Smith, S.W.: Beam steering with linear arrays. IEEE Trans Biomed Eng 30(8), 438–452 (1983)CrossRefGoogle Scholar
  2. 2.
    Harput, S., Bozkurt, A.: Ultrasonic phased array device for acoustic imaging in air. IEEE Sens J 8(11), 1755–1762 (2008)CrossRefGoogle Scholar
  3. 3.
    Luo, Y., Lu, X., Wang, K., Wang, L.: The application in detection of defects in compound material with ultrasonic phased array technology. In: Proceeding of the 26th Chinese control and decision conference (CCDC), pp. 2100–2103, May 31–June 2, 2014Google Scholar
  4. 4.
    Hosono, Y., Yamashita, Y.: Piezoelectric ceramics with high dielectric constants for ultrasonic medical transducers. IEEE Trans Ultrason Ferroelectr Freq Contr 52(10), 1823–1828 (2005)CrossRefGoogle Scholar
  5. 5.
    Drinkwater, B.W., Wilcox, P.D.: Ultrasonic arrays for non-destructive evaluation: a review. NDT E Int. 39(7), 525–541 (2006)CrossRefGoogle Scholar
  6. 6.
    Li, Y., Robinson, B.: The cross algorithm for phase-aberration correction in medical ultrasound images formed with two-dimensional arrays. IEEE Trans Ultrason Ferroelectr Freq Control 55(3), 588–601 (2008)CrossRefGoogle Scholar
  7. 7.
    De Andrade Maia, O.M., Schneider, F.K., Maia, J.M., Comar Neves, L., Do Rocio Chiarello Penteado, S.: Wood characterization using the power spectral density and phase velocity of ultrasonic signals. In: Proceeding of IEEE international ultrasonics symposium (IUS), pp. 1416–1419, 3–6 Sept. 2014Google Scholar
  8. 8.
    Yang, J.S., Zhao, X.G., Zhang, Y.J., Cao, Z.: A new type of wheeled intelligent ultrasonic thickness measurement system. In: Symposium on piezoelectricity, acoustic waves and device applications (SPAWDA), pp. 1–4, 25–27 Oct. 2013Google Scholar
  9. 9.
    Lines, D.I.A., Pettigrew, I.G., Kirk, K.J., Cochran, S., Skramstad, J.A.: Rapid distributed data collection and processing with arrays—the next step beyond full waveform capture. In: The 44th annual British conference on NDT, vol. 48, no. 2, pp. 84–88. September 2005Google Scholar
  10. 10.
    Jensen, J.A., Nikolov, S.I., Gammelmark, K.L., Pedersen, M.H.: Synthetic aperture ultrasound imaging. Ultrasonics 44, e5–e15 (2006)CrossRefGoogle Scholar
  11. 11.
    Nikolov, S.I., Jensen, J.A., Tomov, B.G.: Fast parametric beamformer for synthetic aperture imaging. IEEE Trans Ultrason Ferroelectr Freq Control 55(8), 1755–1767 (2008)CrossRefGoogle Scholar
  12. 12.
    Holmes, C., Drinkwater, B.W., Wilcox, P.D.: Post-processing of the full matrix of ultrasonic transmit–receive array data for non-destructive evaluation. NDT E Int. 38(8), 701–711 (2005)CrossRefGoogle Scholar
  13. 13.
    Holmes, C., Drinkwater, B.W., Wilcox, P.D.: Advanced post-processing for scanned ultrasonic arrays: application to defect detection and classification in non-destructive evaluation. Ultrasonics 48, 636–642 (2005)CrossRefGoogle Scholar
  14. 14.
    Jensen, J.A., Hansen, M., Tomov, B.G., Nokolov, S.I., Holten-Lund, H.: System architecture of an experimental synthetic aperture real-time ultrasound system. IEEE ultrasonics symposium, pp. 636–640 (2007)Google Scholar
  15. 15.
    Lines, D., Wharrie, J., Hottenroth, J., Skramstad, J., Goodman, R., Wood, N.: Real-time ultrasonic array imaging using full matrix capture and the total focusing method. In: Proceedings of 2nd aircraft airworthiness and sustainment conference, San Diego, 18–21 April 2011Google Scholar
  16. 16.
    Lambert, J., Pedron, A., Gens, G., Bimbard, F., Lacassagne, L., Iakovleva, E.: Performance evaluation of total focusing method on GPP and GPU. In: Conference on design and architectures for signal and image processing (DASIP), pp. 1–8, 23–25 Oct 2012Google Scholar
  17. 17.
    Sutcliffe, M., Weston, M., Dutton, B., Charlton, P., Donne, K.: Real-time full matrix capture for ultrasonic non-destructive testing with acceleration of post-processing through graphic hardware. NDT E Int. 51, 16–23 (2012)CrossRefGoogle Scholar
  18. 18.
    Charlton, P., Sutcliffe, M., Weston, M., Cooper, I., Donne, K.: Full matrix capture with time efficient auto focusing of unknown geometry through dual-layered media. Insight (Br. J. NDT), 55(6) (2013)Google Scholar
  19. 19.
    CIVA. Simulation software for non destructive testing.
  20. 20.
    MultiX++: PAUT equipment for NDT application.
  21. 21.
  22. 22.
    Todorovich, E., Dai Pra, A.L., Passoni, L.I., Vázquez, M., Cozzolino, E., Ferrara, F., Bioul, B.: Real-time speckle image processing. J Real Time Image Proc. (2013). doi: 10.1007/s11554-013-0343-4 Google Scholar
  23. 23.
    Bahri, N., Grandpierre, T., Masmoudi, N., Akil, M., Sorel, Y.: Optimization of real time application on mixed architecture using AAA methodology extension. Int J Electr Commun Comput Eng 4(5), 1455–1466 (2013)Google Scholar
  24. 24.
    Czechowski, K., Vuduc, R.: A theoretical framework for algorithm-architecture co-design. In: IEEE 27th international symposium on parallel and distributed processing (IPDPS), pp. 791–802, 20–24 May 2013. doi: 10.1109/IPDPS.2013.99
  25. 25.
    Njiki M., Elouardi, A., Bouaziz, S., Casula, O., Roy, O.: A real-time implementation of the total focusing method for rapid and precise diagnostic in non destructive evaluation. IEEE 24th international conference on application-specific systems, architectures and processors (ASAP), 2013Google Scholar
  26. 26.
    Bannouf, S., Robert, S., Casula, O., Prada, C.: Data set reduction for ultrasonic TFM imaging using the effective aperture approach and virtual sources. J Phys Conf Ser 457(1), 0120071 (2013)Google Scholar
  27. 27.
    Cruza, J.F., Perez, M., Moreno, J.M., Fritsch, C.: Real time fast ultrasound imaging technology and possible applications. Phys Proc 63, 79–84 (2015)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.M2M-NDTLes UlisFrance
  2. 2.IEF, UMR 8622 Univ Paris-SudUniversité Paris SaclayOrsayFrance
  3. 3.CEA LISTGif-sur-YvetteFrance

Personalised recommendations