Apodization scheme for hardware-efficient beamformer

3D ultrasound is an emerging diagnostic technique that extends standard ultrasound imaging by capturing volumes, instead of planes. This brings completely new diagnostic opportunities, among which the possibility of disjoining image acquisition and analysis, thus enabling remote diagnosis, which would bring obvious medical and economic benefits. Unfortunately, 3D ultrasound is several orders of magnitude more computationally complex than 2D imaging. Therefore, algorithmic improvements to simplify the processing are mandatory in order to conceive cheap, portable, low-power imagers. The kernel of the 3D imaging process, called beamforming, consists essentially of computing delay and apodization profiles. We have previously devised an approximation of the delay calculation stage, which dramatically reduces hardware complexity. Unfortunately, this approximation introduces an intrinsic degree of inaccuracy that can be characterized as added image noise. In this paper, we identify an efficient approximated approach to the calculation of apodization profiles, that additionally minimizes (-76%) the error introduced during delay calculation. Together, these two techniques enable an efficient computation of 3D ultrasound images.

[1]  J. Arendt Paper presented at the 10th Nordic-Baltic Conference on Biomedical Imaging: Field: A Program for Simulating Ultrasound Systems , 1996 .

[2]  Ming Yang,et al.  Sonic Millip3De: A massively parallel 3D-stacked accelerator for 3D ultrasound , 2013, 2013 IEEE 19th International Symposium on High Performance Computer Architecture (HPCA).

[3]  P. Mandal,et al.  Real time dynamic receive apodization for an ultrasound imaging system , 2006, 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (VLSID'06).

[4]  J. Jensen,et al.  Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers , 1992, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[5]  Luca Benini,et al.  Tackling the bottleneck of delay tables in 3D ultrasound imaging , 2015, 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[6]  Jørgen Arendt Jensen,et al.  Compact implementation of dynamic receive apodization in ultrasound scanners , 2004, SPIE Medical Imaging.

[7]  B. Savord,et al.  Fully sampled matrix transducer for real time 3D ultrasonic imaging , 2003, IEEE Symposium on Ultrasonics, 2003.

[8]  Matthias Bo Stuart,et al.  Performance of SARUS: A synthetic aperture real-time ultrasound system , 2010, 2010 IEEE International Ultrasonics Symposium.

[9]  P. J. 't Hoen Aperture apodization to reduce the off-axis intensity of the pulsed-mode directivity function of linear arrays , 1982 .

[10]  S. I. Nikolov,et al.  SARUS: A synthetic aperture real-time ultrasound system , 2013, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[11]  Jørgen Arendt Jensen,et al.  Recursive delay calculation unit for parametric beamformer , 2006, SPIE Medical Imaging.

[12]  J.A. Jensen,et al.  Fast parametric beamformer for synthetic aperture imaging , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[13]  W. E. Engeler,et al.  Windowing of wide-band ultrasound transducers , 1996, 1996 IEEE Ultrasonics Symposium. Proceedings.

[14]  Luca Benini,et al.  Efficient parallel beamforming for 3D ultrasound imaging , 2014, GLSVLSI '14.

[15]  Jin Ho Chang,et al.  Efficient implementation of a real-time dynamic synthetic aperture beamformer , 2012, 2012 IEEE International Ultrasonics Symposium.

[16]  K. Boone,et al.  Effect of skin impedance on image quality and variability in electrical impedance tomography: a model study , 1996, Medical and Biological Engineering and Computing.