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A comprehensive comparison of GPU- and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography

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Abstract

As today’s standard screening methods frequently fail to diagnose breast cancer before metastases have developed, earlier breast cancer diagnosis is still a major challenge. Three-dimensional ultrasound computer tomography promises high-quality images of the breast, but is currently limited by a time-consuming image reconstruction. In this work, we investigate the acceleration of the image reconstruction by GPUs and FPGAs. We compare the obtained performance results with a recent multi-core CPU. We show that both architectures are able to accelerate processing, whereas the GPU reaches the highest performance. Furthermore, we draw conclusions in terms of applicability of the accelerated reconstructions in future clinical application and highlight general principles for speed-up on GPUs and FPGAs.

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  1. Available online at http://opencores.com/project,pcie_sg_dma.

References

  1. Asano, S., Maruyama, T., Yamaguchi, Y.: Performance comparison of FPGA, GPU and CPU in image processing. In: International Conference on Field Programmable Logic and Applications, FPL, pp. 126–131 (2009)

  2. Birk, M., Hagner, C., Balzer, M., Ruiter, N.V., Huebner, M., Becker, J.: Evaluation of the reconfiguration of the data acquisition system for 3D USCT. Int. J. Reconfigurable Comput. 2011, 9 (2011)

    Article  Google Scholar 

  3. Brodtkorb, A.R., Dyken, C., Hagen, T.R., Hjelmervik, J.M., Storaasli, O.O.: State-of-the-art in heterogeneous computing. Sci. Progr. 18, 1–33 (2010)

    Google Scholar 

  4. Chase, J., Nelson, B., Bodily, J., Wei, Z., Lee, D.J.: Real-time optical flow calculations on FPGA and GPU architectures: a comparison study. In: 16th International Symposium on field-programmable custom computing machines, FCCM ’08., pp. 173–182 (2008)

  5. Cyclone II Device Handbook. Tech. rep., Altera Corporation (2007). http://www.altera.com/literature/hb/cyc2/cyc2_cii5v1.pdf (online, accessed 28-Feb-2012)

  6. Che, S., Li, J., Sheaffer, J., Skadron, K., Lach, J.: Accelerating compute-intensive applications with GPUs and FPGAs. In: Symposium on Application Specific Processors, SASP, pp. 101–107 (2008)

  7. Doctor, S., Hall, T., Reid, L.: SAFT the evolution of a signal processing technology for ultrasonic testing. NDT Int. 19(3), 163–167 (1986)

    Article  Google Scholar 

  8. Ferlay, J., Shin, H., Bray, F., Forman, D., Mathers, C., Parkin, D.: GLOBOCAN 2008 v1.2, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 10”. Tech. rep., International Agency for Research on Cancer, Lyon. http://globocan.iarc.fr (Internet, accessed 20-Feb-2012)

  9. Gemmeke, H., Berger, L., Birk, M., Goebel, G., Menshikov, A., Tcherniakhovski, D., Zapf, M., Ruiter, N.: Hardware setup for the next generation of 3D ultrasound computer tomography. In: IEEE Nuclear Science Symposium Conference Record (NSS/MIC), pp. 2449–2454 (2010)

  10. Heigl, B., Kowarschik, M.: High-speed reconstruction for C-arm computed tomography. In: Proceedings of the 9th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and, Nuclear Medicine, pp. 25–28 (2007)

  11. Jensen, J., Hansen, M., Tomov, B., Nikolov, S., Holten-Lund, H.: 8A–3 System Architecture of an Experimental Synthetic Aperture Real-Time Ultrasound System. In: Ultrasonics Symposium, IEEE pp. 636–640 (2007)

  12. Intel Microarchitecture Codename Nehalem. Tech. rep., Intel Corporation. http://www.intel.com/technology/architecture-silicon/next-gen/index.htm (online, accessed 20-Feb-2012)

  13. Kalarot, R., Morris, J.: Comparison of FPGA and GPU implementations of real-time stereo vision. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 9–15 (2010)

  14. Marcus, G., Gao, W., Kugel, A., Manner, R.: The MPRACE framework: an open source stack for communication with custom FPGA-based accelerators. In: VII Southern Conference on Programmable Logic (SPL), pp. 155–160 (2011)

  15. Nickolls, J., Dally, W.: The GPU computing era. Micro. IEEE 30(2), 56–69 (2010)

    Article  Google Scholar 

  16. Nol, P.B., Walczak, A.M., Xu, J., Corso, J.J., Hoffmann, K.R., Schafer, S.: GPU-based cone beam computed tomography. Comput. Methods Progr. Biomed. 98(3), 271–277 (2010)

    Article  Google Scholar 

  17. Norton, S.J., Linzer, M.: Ultrasonic reflectivity imaging in three dimensions: reconstruction with spherical transducer arrays. Ultrason. Imag. 1(3), 210–231 (1979)

    Google Scholar 

  18. Romero, D., Martinez-Graullera, O., Martin, C., Higuti, R., Octavio, A.: Using GPUs for beamforming acceleration on SAFT imaging. In: IEEE International Ultrasonics Symposium (IUS), pp. 1334–1337 (2009)

  19. Ruiter, N., Schwarzenberg, G., Zapf, M., Gemmeke, H.: Improvement of 3D ultrasound computer tomography images by signal pre-processing. In: IEEE Ultrasonics Symposium, IUS 2008, pp. 852–855 (2008)

  20. Ruiter, N.V., Goebel, G., Berger, L., Zapf, M., Gemmeke, H.: Realization of an optimized 3D. USCT 7968(1), 796–805 (2011)

    Google Scholar 

  21. Sorokin, N.: Parallel backprojector for cone-beam computer tomography. In: International Conference on Reconfigurable Computing and FPGAs, ReConFig ’08, pp. 175–180 (2008)

  22. Stone, S., Haldar, J., Tsao, S., Hwu, WmW, Sutton, B., Liang, Z.P.: Accelerating advanced MRI reconstructions on GPUs. J. Parallel Distributed Comput. 68(10), 1307–1318 (2008)

    Article  Google Scholar 

  23. Wu, X.L., Zhuo, Y., Gai, J., Lam, F., Fu, M., Haldar, J.P., Hwu, W.M., Liang, Z.P., Sutton, B.P.: Advanced MRI reconstruction toolbox with accelerating on GPU. Proc SPIE 7872(1), 78720Q (2011)

    Article  Google Scholar 

  24. Xilinx Virtex-6 Documentation. Tech. rep., Xilinx Corporation. http://www.xilinx.com/support/documentation/virtex-6.htm (online, accessed 20-Feb-2012)

  25. Zapf, M., Schwarzenberg, G.F., Ruiter, N.V.: High throughput SAFT for an experimental USCT system as MATLAB implementation with use of SIMD CPU instructions. Proc SPIE 6920, 692010–692011 (2008).

    Google Scholar 

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Authors and Affiliations

  1. Institute for Data Processing and Electronics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Matthias Birk, Michael Zapf, Matthias Balzer & Nicole Ruiter

  2. Institute for Information Processing Technology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Jürgen Becker

Authors
  1. Matthias Birk
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  2. Michael Zapf
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  3. Matthias Balzer
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  4. Nicole Ruiter
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  5. Jürgen Becker
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Correspondence to Matthias Birk.

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This work has partly been funded by Deutsche Forschungsgemeinschaft.

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Birk, M., Zapf, M., Balzer, M. et al. A comprehensive comparison of GPU- and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography. J Real-Time Image Proc 9, 159–170 (2014). https://doi.org/10.1007/s11554-012-0267-4

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