An ultrasonic imaging system based on a new SAFT approach and a GPU beamformer

The design of newer ultrasonic imaging systems attempts to obtain low-cost, small-sized devices with reduced power consumption that are capable of reaching high frame rates with high image quality. In this regard, synthetic aperture techniques have been very useful. They reduce hardware requirements and accelerate information capture. However, the beamforming process is still very slow, limiting the overall speed of the system. Recently, general-purpose computing on graphics processing unit techniques have been proposed as a way to accelerate image composition. They provide excellent computing power with which a very large volume of data can easily and quickly be processed. This paper describes a new system architecture that merges both principles. Thus, using a minimum-redundancy synthetic aperture technique to acquire the signals (2R-SAFT), and a graphics processing unit as a beamformer, we have developed a new scanner with full dynamic focusing, both on emission and reception, that attains real-time imaging with very few resources.

[1]  M. O'Donnell,et al.  Synthetic aperture imaging for small scale systems , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[2]  G. R. Lockwood,et al.  Optimizing sparse two-dimensional transducer arrays using an effective aperture approach , 1994, 1994 Proceedings of IEEE Ultrasonics Symposium.

[3]  G. S. Kino,et al.  Real Time Synthetic Aperture Imaging System , 1980 .

[4]  R. Y. Chiao,et al.  Aperture formation on reduced-channel arrays using the transmit-receive apodization matrix , 1996, 1996 IEEE Ultrasonics Symposium. Proceedings.

[5]  Richard J. Kozick,et al.  Coarray synthesis with circular and elliptical boundary arrays , 1992, IEEE Trans. Image Process..

[6]  Peter T. Gough,et al.  Unified framework for modern synthetic aperture imaging algorithms , 1997, Int. J. Imaging Syst. Technol..

[7]  R. T. Hoctor,et al.  The unifying role of the coarray in aperture synthesis for coherent and incoherent imaging , 1990, Proc. IEEE.

[8]  Stephen W. Smith,et al.  Beam Steering with Linear Arrays , 1983, IEEE Transactions on Biomedical Engineering.

[9]  Kevin Skadron,et al.  Scalable parallel programming , 2008, 2008 IEEE Hot Chips 20 Symposium (HCS).

[10]  Jie Cheng,et al.  Programming Massively Parallel Processors. A Hands-on Approach , 2010, Scalable Comput. Pract. Exp..

[11]  Jr. S. Marple,et al.  Computing the discrete-time 'analytic' signal via FFT , 1999, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[12]  David P. Luebke,et al.  CUDA: Scalable parallel programming for high-performance scientific computing , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[13]  Gordon S. Kino,et al.  A real-time, synthetic-aperture, digital acoustic imaging system , 1982 .

[14]  Martín Arguedas,et al.  Técnicas de apertura sintética para la generación de imagen ultrasónica , 2010 .

[15]  John E. Stone,et al.  OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems , 2010, Computing in Science & Engineering.

[16]  David Romero-Laorden,et al.  Field modelling acceleration on ultrasonic systems using graphic hardware , 2011, Comput. Phys. Commun..