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Parallel Iterative CT Image Reconstruction on a Linux Cluster of Legacy Computers

In: Current Trends in High Performance Computing and Its Applications

Author

Listed:
  • Xiang Li

    (University of Iowa, Center for Statistical Genetics Research)

  • Jun Ni

    (University of Iowa, Center for Statistical Genetics Research)

  • Tao He

    (University of Iowa, Center for Statistical Genetics Research)

  • Ge Wang

    (University of Iowa, Center for Statistical Genetics Research)

  • Shaowen Wang

    (University of Iowa, Center for Statistical Genetics Research)

  • Body Knosp

    (University of Iowa, Center for Statistical Genetics Research)

Abstract

Summary The expectation maximization (EM) algorithm is one of the iterative reconstruction (IR) algorithms that enable to reconstruct superior CT images, compared with the conventional filtered back-projection (FBP) method. The EM-IR algorithm can also be used when the data is incomplete. The major disadvantage of the EM-IR is its high demand on computation and slow reconstruction. To improve the performance, we developed a parallel EM on a Linux cluster composed of legacy (recycled) and heterogeneous PCs. The system, speed-up and efficiency from our parallel computations are presented. The study provides basic insight into how to conduct medical image reconstruction using junk PCs to simulate a heterogeneous parallel system.

Suggested Citation

  • Xiang Li & Jun Ni & Tao He & Ge Wang & Shaowen Wang & Body Knosp, 2005. "Parallel Iterative CT Image Reconstruction on a Linux Cluster of Legacy Computers," Springer Books, in: Wu Zhang & Weiqin Tong & Zhangxin Chen & Roland Glowinski (ed.), Current Trends in High Performance Computing and Its Applications, pages 369-373, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27912-9_46
    DOI: 10.1007/3-540-27912-1_46
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