
Proceedings Paper
Iterative reconstruction of cone-beam CT data on a clusterFormat | Member Price | Non-Member Price |
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Paper Abstract
Three-dimensional iterative reconstruction of large CT data sets poses several challenges in terms of the associated
computational and memory requirements. In this paper, we present results obtained by implementing
a computational framework for reconstructing axial cone-beam CT data using a cluster of inexpensive dualprocessor
PCs. In particular, we discuss our parallelization approach, which uses POSIX threads and message
passing (MPI) for local and remote load distribution, as well as the interaction of that load distribution with
the implementation of ordered subset based algorithms. We also consider a heuristic data-driven 3D focus of
attention algorithm that reduces the amount of data that must be considered for many data sets. Furthermore,
we present a modification to the SIRT algorithm that reduces the amount of data that must be communicated
between processes. Finally, we introduce a method of separating the work in such a way that some computation
can be overlapped with the MPI communication thus further reducing the overall run-time. We summarize the
performance results using reconstructions of experimental data.
Paper Details
Date Published: 28 February 2007
PDF: 9 pages
Proc. SPIE 6498, Computational Imaging V, 64980Q (28 February 2007); doi: 10.1117/12.716675
Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)
PDF: 9 pages
Proc. SPIE 6498, Computational Imaging V, 64980Q (28 February 2007); doi: 10.1117/12.716675
Show Author Affiliations
Thomas M. Benson, GE Global Research (United States)
Jens Gregor, The Univ. of Tennessee, Knoxville (United States)
Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)
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