Portable parallel kernels for high-speed beamforming in synthetic aperture ultrasound imaging

In medical ultrasound, synthetic aperture (SA) imaging is well-considered as a novel image formation technique for achieving superior resolution than that offered by existing scanners. However, its intensive processing load is known to be a challenging factor. To address such a computational demand, this paper proposes a new parallel approach based on the design of OpenCL signal processing kernels that can compute SA image formation in real-time. We demonstrate how these kernels can be ported onto different classes of parallel processors, namely multi-core CPUs and GPUs, whose multi-thread computing resources are able to process more than 250 fps. Moreover, they have strong potential to support the development of more complex algorithms, thus increasing the depth range of the inspected human volume and the final image resolution observed by the medical practitioner.

[1]  Satnam Singh Computing without processors , 2012, CODES+ISSS '12.

[2]  David Kaeli,et al.  Heterogeneous Computing with OpenCL , 2011 .

[3]  J.A. Jensen,et al.  8A-3 System Architecture of an Experimental Synthetic Aperture Real-Time Ultrasound System , 2007, 2007 IEEE Ultrasonics Symposium Proceedings.

[4]  Junying Chen,et al.  Medical Ultrasound Imaging: To GPU or Not to GPU? , 2011, IEEE Micro.

[5]  G. R. Lockwood,et al.  Theoretical assessment of a synthetic aperture beamformer for real-time 3-D imaging , 1998, 1998 IEEE Ultrasonics Symposium. Proceedings (Cat. No. 98CH36102).

[6]  G York,et al.  Ultrasound processing and computing: review and future directions. , 1999, Annual review of biomedical engineering.

[7]  Leonel Sousa,et al.  Portable LDPC Decoding on Multicores Using OpenCL [Applications Corner] , 2012, IEEE Signal Processing Magazine.

[8]  J. A. Jensen,et al.  Recursive ultrasound imaging , 1999, 1999 IEEE Ultrasonics Symposium. Proceedings. International Symposium (Cat. No.99CH37027).

[9]  Yen-Kuang Chen,et al.  Challenges and opportunities of obtaining performance from multi-core CPUs and many-core GPUs , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[10]  B. Y. S. Yiu,et al.  GPU-based beamformer: Fast realization of plane wave compounding and synthetic aperture imaging , 2011, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[11]  Konstantinos N. Plataniotis,et al.  Parallelization and performance of 3D ultrasound imaging beamforming algorithms on modern clusters , 2002, ICS '02.

[12]  G.R. Lockwood,et al.  Theoretical assessment of a synthetic aperture beamformer for real-time 3-D imaging , 1999, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[13]  Jørgen Arendt Jensen,et al.  Synthetic aperture ultrasound imaging. , 2006, Ultrasonics.