Logo image
Back
Parallelism of iterative CT reconstruction based on local reconstruction algorithm
Journal article   Peer reviewed

Parallelism of iterative CT reconstruction based on local reconstruction algorithm

Junjun Deng, Hengyong Yu, Jun Ni, Lihe Wang and Ge Wang
The Journal of supercomputing, Vol.48(1), pp.1-14
04/01/2009
DOI: 10.1007/s11227-008-0198-9
PMCID: PMC2901129
PMID: 20622984
url
https://www.ncbi.nlm.nih.gov/pmc/articles/2901129View
Open Access

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 (Li et al. in J. X-Ray Sci. Technol. 13:1-10, 2005). To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm (Wang et al. in Scanning 18:582-588, 1996 and IEEE Trans. Med. Imaging 15(5):657-664, 1996). The object to be reconstructed is partitioned into a number of subregions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the subregion. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom (Lauritsch and Bruder http://www.imp.uni-erlangen.de/phantoms/head/head.html) 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.
 Computer Science Computer Science, Hardware & Architecture Computer Science, Theory & Methods Engineering Engineering, Electrical & Electronic Science & Technology Technology

Details

Metrics

15 Record Views
5 Times Cited - Web of Science
Logo image