Objective
The objective of this study was to reduce metal-induced streak artifact on oral and
maxillofacial x-ray computed tomography (CT) images by developing the fast statistical
image reconstruction system using iterative reconstruction algorithms.
Study Design
Adjacent CT images often depict similar anatomical structures in thin slices. So,
first, images were reconstructed using the same projection data of an artifact-free
image. Second, images were processed by the successive iterative restoration method
where projection data were generated from reconstructed image in sequence. Besides
the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation
maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI)
setting and reverse processing were applied for improving performance.
Results
Both algorithms reduced artifacts instead of slightly decreasing gray levels. The
OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential
and reverse processing did not show apparent effects.
Conclusions
Two alternatives in iterative reconstruction methods were effective for artifact reduction.
The OS-EM algorithm and small ROI setting improved the performance.
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Article info
Publication history
Published online: October 02, 2012
Accepted:
July 23,
2012
Received in revised form:
July 12,
2012
Received:
May 3,
2012
Footnotes
Our joint research project was partly supported by the Bilateral Program of the Japan Society for the Promotion of Science, 2010-2012.
Identification
Copyright
© 2012 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
