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A Parallel Implementation of the Katsevich Algorithm for 3-D CT Image Reconstruction

Published: 01 October 2006 Publication History

Abstract

Yu and Wang [1, 2] implemented the first theoretically exact spiral cone-beam reconstruction algorithm developed by Katsevich [3, 4]. This algorithm requires a high computational cost when the data amount becomes large. Here we study a parallel computing scheme for the Katsevich algorithm to facilitate the image reconstruction. Based on the proposed parallel algorithm, several numerical tests are conducted on a high performance computing (HPC) cluster with thirty two 64-bit AMD-based Opteron processors. The standard phantom data [5] is used to establish the performance benchmarks. The results show that our parallel algorithm significantly reduces the reconstruction time, achieving high speedup and efficiency.

References

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Cited By

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  • (2011)Speedup performance analysis of parallel Katsevich algorithm for 3D CT image reconstructionInternational Journal of Computational Science and Engineering10.1504/IJCSE.2011.0420186:3(151-159)Online publication date: 1-Aug-2011
  • (2010)Fast katsevich algorithm based on GPU for helical cone-beam computed tomographyIEEE Transactions on Information Technology in Biomedicine10.1109/TITB.2009.203636814:4(1053-1061)Online publication date: 1-Jul-2010

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Published In

cover image The Journal of Supercomputing
The Journal of Supercomputing  Volume 38, Issue 1
October 2006
103 pages

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Kluwer Academic Publishers

United States

Publication History

Published: 01 October 2006

Author Tags

  1. Computed tomography (CT)
  2. Katsevich algorithm
  3. MPI
  4. high performance computing
  5. image reconstruction
  6. medical imaging
  7. parallel computing
  8. spiral cone-beam CT

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  • (2011)Speedup performance analysis of parallel Katsevich algorithm for 3D CT image reconstructionInternational Journal of Computational Science and Engineering10.1504/IJCSE.2011.0420186:3(151-159)Online publication date: 1-Aug-2011
  • (2010)Fast katsevich algorithm based on GPU for helical cone-beam computed tomographyIEEE Transactions on Information Technology in Biomedicine10.1109/TITB.2009.203636814:4(1053-1061)Online publication date: 1-Jul-2010

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