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Proceedings Paper

Parallelism of iterative CT algorithm based on local reconstruction
Author(s): Junjun Deng; Hengyong Yu; Jun Ni; Lihe Wang; Ge Wang
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Paper Abstract

An iterative algorithm is suited to reconstruct CT images from noisy or truncated projection data. However, as a disadvantage, the algorithm requires significant computational time. Although a parallel technique can be used to reduce the computational time, a large amount of communication overhead becomes an obstacle to its performance. To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm. The object to be reconstructed is partitioned into a number of sub-regions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the sub-region. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom was used as benchmark to measure the parallel performance. The experimental results showed that the proposed parallel algorithm significantly reduces the reconstruction time, hence achieving a high speedup and efficiency.

Paper Details

Date Published: 7 September 2006
PDF: 10 pages
Proc. SPIE 6318, Developments in X-Ray Tomography V, 63181P (7 September 2006); doi: 10.1117/12.681272
Show Author Affiliations
Junjun Deng, Univ. of Iowa (United States)
Hengyong Yu, Univ. of Iowa (United States)
Jun Ni, Univ. of Iowa (United States)
Lihe Wang, Univ. of Iowa (United States)
Ge Wang, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 6318:
Developments in X-Ray Tomography V
Ulrich Bonse, Editor(s)

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