Keywords:
Cone-Beam CT, 4D-CBCT reconstruction, MKB algorithm, joint projection data
Although the quality of the phase-resolved reconstruction images could be improved by the four-dimensional cone-beam computed tomography (4D-CBCT) by reducing the motion blurring artifacts, it may still be degraded by severe viewaliasing artifacts because of highly under-sampled projections at each phase. Inspired by the strong correlation between different phase-resolved reconstructed images, we present a simple and effective approach to estimate a set of full-sampled projections for every individual respiratory phase and then to incorporate them into the 4D-CBCT iterative reconstruction scheme. In the implementation of the 4D-CBCT iterative reconstruction scheme,a coupled distance-driven forward and backward projection operator via GPU is introduced. The proposed method has been tested in a digital XCAT phantom and a clinical patient case. Quantitative evaluations indicate that a 15.7% and 9.9%decrease in the root-mean-square error (RMSE) are achieved by our method when comparing with the conventional 4D-CBCT reconstruction method and the classic McKinnon/Bates algorithm (MKB), respectively. At the same time, our method is also valid by calculating the contrast-to-noise ratio (CNR) of a region of interest (ROI). The result shows that the CNR of our method is 1.34, which is better than that of the MKB algorithm.
- Shaohua Zhi
- Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, China
- Xuanqin Mou
- Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, China
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