Skip to main content
SpringerLink
Log in

Fast implementation of area integral model SART algorithm based on look-up table

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

Forward projection and back-projection are two computationally intense operations in simultaneous algebraic reconstruction technique (SART), especially for area integral model (AIM). We have proposed a fast forward projection algorithm for AIM-based algebraic reconstruction technique, which can be used to accelerate the forward projection operation of area integral model SART. However, the back-projection operation is extremely time-consuming due to its complexity. In this paper, we propose a fast approach to improve the reconstruction speed of AIM-based SART algorithm. To avoid repeated computation of the intersection between rays and pixels, we construct three look up tables (LUTs) to store the number of rays that intersecting with a given pixel, and the corresponding ray indices and weighting factors, respectively, which can be done during the forward projection operation. In the back-projection operation, we update pixels value using these LUTs. On this basis, we utilize the multi-threading technique to implement the forward projection and back-projection operations on a multi-core platform. Experimental results show that the proposed LUT-based approach with multi-core acceleration achieves a speedup of 36.5 times over the conventional approach, and preserves accuracy of the results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Andersen, A.H., Kak, A.C.: Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm. Ultrason. Imaging 6(1), 81–94 (1984)

    Article  Google Scholar 

  2. Hu, J., Zhao, X., Wang, F.: An extended simultaneous algebraic reconstruction technique (E-SART) for X-ray dual spectral computed tomography. Scanning 38(6), 599–611 (2016)

    Article  Google Scholar 

  3. Kim, J.K., Fessler, J.A., Zhang, Z.: Forward-projection architecture for fast iterative image reconstruction in X-ray CT. IEEE Trans. Signal Process. 60(10), 5508–5518 (2012)

    Article  MathSciNet  Google Scholar 

  4. Siddon, R.L.: Fast calculation of the exact radiological path for a three-dimensional CT array. Med. Phys. 12(2), 252–255 (1985)

    Article  Google Scholar 

  5. Jacobs, F., Sundermann, E., Sutter, B.D., Christiaens, M., Lemahieu, I.: A fast algorithm to calculate the exact radiological path through a pixel or voxel space. J. Comput. Inf. Technol. 6(1), 89–94 (1998)

    Google Scholar 

  6. Zhao, H., Reader, A.J.: Fast projection algorithm for voxel arrays with object dependent boundaries. IEEE Nucl. Sci. Symp. Conf. Rec. 3(3), 1490–1494 (2002)

    Google Scholar 

  7. Mueller, K., Yagel, R.: Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware. IEEE Trans. Med. Imaging 19(12), 1227–1237 (2002)

    Article  Google Scholar 

  8. Liu, B., Zeng, Li: Parallel SART algorithm of linear scan cone-beam CT for fixed pipeline. J. X-Ray Sci. Technol. 17(3), 221–232 (2009)

    MathSciNet  Google Scholar 

  9. Pang, W., Qin, J., Lu, Y., Xie, Y., Chui, C., Heng, P.: Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU. Int. J. Comput. Assist. Radiol. Surg. 6(2), 187–199 (2011)

    Article  Google Scholar 

  10. Li, X., Ni, J., Wang, G.: Parallel iterative cone beam CT image reconstruction on a PC cluster. J. X-Ray Sci. Technol. 13(2), 1–10 (2005)

    Google Scholar 

  11. Zeng, G.L., Gullberg, G.T.: A study of reconstruction artifacts in cone beam tomography using filtered backprojection and iterative EM algorithms. IEEE Trans. Nucl. Sci. 37(2), 759–767 (1990)

    Article  Google Scholar 

  12. Yu, H., Wang, G.: Finite detector based projection model for high spatial resolution. J. X-Ray Sci. Technol. 20(2), 229–238 (2012)

    MathSciNet  Google Scholar 

  13. Zhang, S., Zhang, D., Gong, H., Ghasemalizadeh, O., Wang, Ge, Cao, G.: Fast and accurate computation of system matrix for area integral model-based algebraic reconstruction technique. Opt. Eng. 53(3), 113101–113109 (2014)

    Article  Google Scholar 

  14. Li, N., Zhao, H.X., Cho, S.H., Choi, J.G., Kim, M.H.: A fast algorithm for voxel-based deterministic simulation of X-ray imaging. Comput. Phys. Commun. 178(7), 518–523 (2008)

    Article  Google Scholar 

  15. Hong, I.K., Chung, S.T., Kim, H.K., Kim, Y.B., Son, Y.D., Cho, Z.H.: Ultra fast symmetry and SIMD-based projection-backprojection (SSP) algorithm for 3-D PET image reconstruction. IEEE Trans. Med. Imag. 26(6), 789–803 (2007)

    Article  Google Scholar 

  16. Zhu, X., Li, K., Salah, A.: A data parallel strategy for aligning multiple biological sequences on multi-core computers. Comput. Biol. Med. 43(4), 350–361 (2013)

    Article  Google Scholar 

  17. Jia, X., Dong, B., Lou, Y., Jiang, S.B.: GPU-based iterative cone-beam CT reconstruction using tight frame regularization. Phys. Med. Biol. 56(13), 3787–3807 (2011)

    Article  Google Scholar 

  18. Xu, D., Huang, Y., Kang, J.U.: GPU-accelerated non-uniform fast Fourier transform-based compressive sensing spectral domain optical coherence tomography. Opt. Express 22(12), 14871–14884 (2014)

    Article  Google Scholar 

  19. Jia, X., Ziegenhein, P., Jiang, S.B.: GPU-based high-performance computing for radiation therapy. Phys. Med. Biol. 59(4), 151–182 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the National Natural Science Foundation of China (Grant: 61772421, 61572400, 61731015, 61602380).

Author information

Authors and Affiliations

  1. School of Information Science and Technology, Northwest University, Xi’an, 710127, Shaanxi, China

    Shunli Zhang, Guohua Geng, Zhan Li & Yuhe Zhang

Authors
  1. Shunli Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guohua Geng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuhe Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shunli Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, S., Geng, G., Li, Z. et al. Fast implementation of area integral model SART algorithm based on look-up table. Cluster Comput 22 (Suppl 6), 15195–15203 (2019). https://doi.org/10.1007/s10586-018-2533-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-018-2533-0

Keywords

Search

Navigation