Robust moving-blocker scatter correction for cone-beam computed tomography using multiple-view information

Cong Zhao, Xi Chen, Luo Ouyang, Jing Wang and Mingwu Jin

PLOS ONE, 2017, vol. 12, issue 12, 1-19

Abstract: Scatter contamination is one of the main sources of decreasing the image quality in cone-beam computed tomography (CBCT). The moving blocker method is economic and effective for scatter correction (SC), which can simultaneously estimate scatter and reconstruct the complete volume within the field of view (FOV) from a single CBCT scan. However, at the regions with large intensity transition in the projection images along the axial blocker moving direction, the estimation of scatter signal from blocked regions in a single projection view can produce large error and cause significant artifacts in reconstructed images and null the usability of these regions. Furthermore, blocker edge detection error can significantly deteriorate both primary signal and scatter signal estimation and lead to unacceptable reconstruction results. In this study, we propose to use the adjacent multi-view projection images to jointly estimate scatter signal more accurately. In return, the more accurately estimated scatter signal can be utilized to detect blocker edges more accurately for greatly improved robustness of moving-blocker based SC. The experimental results using a Catphan phantom and an anthropomorphic pelvis phantom CBCT data show that the new method can effectively suppress the estimation errors of scatter signal in the fast signal transition regions and is able to correct the blocker detection errors. This development will expand the utility of moving-blocker based SC for the target with sharp intensity changes in the projection images and provide the needed robustness for its clinical translation.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0189620

DOI: 10.1371/journal.pone.0189620

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