Truncation Artifact Reduction in Cone-beam CT using Mixed One-bit Compressive Sensing

Xiaolin Huang, Yan Xia, Yixing Huang, Joachim Hornegger, Jie Yang, Andreas Maier


Published in:Fully3D 2017 Proceedings


truncation correction, compressive sensing, one-bit compressive sensing, C-arm, X-ray
In cone-beam computed tomography (CT), it is not uncommon that the acquired projection data are truncated due to either limited detector size or intentionally reduced field of view (FOV) for dose reduction. The resulting truncation is not compatible to conventional reconstruction algorithms and thus leads to truncation artifacts, e.g., the cupping effect towards the boundary of the FOV and incorrect offset in the Hounsfield unit values of reconstructed voxels. Typical truncation artifact correction schemes involve estimating the truncated projection by extrapolation, e.g., water cylinder extrapolation. But the estimation is heuristic and may not always be accurate. In this paper, we propose to estimate the upper bound of missing data and then use the mixed one-bit compressive sensing (M1bit-CS) to compensate truncation artifacts. Bound estimation is much easier and more accurate than projection value estimation and M1bit-CS yields good reconstruction capability from one-bit information, i.e., the bounding inequality. In numerical experiments on both a phantom and a reprojection of a clinical image, the proposed method shows superior reconstruction results over the standard water cylinder extrapolation.
Xiaolin Huang
Shanghai Jiao Tong University, China
Yan Xia
Stanford University, USA
Yixing Huang
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Joachim Hornegger
Friedrich-Alexander University of Erlangen-Nuremberg, Germany
Jie Yang
Shanghai Jiao Tong University, China
Andreas Maier
Friedrich-Alexander University of Erlangen-Nuremberg, Germany
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