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X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms

Authors :
Ying Guo
Dapeng Shi
Minghua Sun
Peigang Ning
Shaocheng Zhu
Source :
PLoS ONE, Vol 9, Iss 3, p e92568 (2014), PLoS ONE
Publication Year :
2014
Publisher :
Public Library of Science (PLoS), 2014.

Abstract

Objective This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) algorithms in reducing computed tomography (CT) radiation dosages in abdominal imaging. Methods CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP), 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs) of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol) were recorded. Results At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. Conclusions Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.

Details

Language :
English
ISSN :
19326203
Volume :
9
Issue :
3
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....9422b1ffb143f326bee45b126b8df0f8