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

Xiang Li (), Jun Ni (), Tao He (), Ge Wang (), Shaowen Wang () and Body Knosp ()
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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

A chapter in Current Trends in High Performance Computing and Its Applications, 2005, pp 369-373 from Springer

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.

Keywords: medical image processing; image reconstruction; parallel computing; LINUX cluster (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-27912-9_46

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DOI: 10.1007/3-540-27912-1_46

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