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Interior Reconstruction from Truncated Projection Data in Cone-beam Computed Tomography

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Abstract

The interior reconstruction of completely truncated projection data is a frontier research hotspot in cone-beam computed tomography (CBCT) application. It is difficult to find a method with acceptable accuracy and high efficiency to solve it. Based on the simplified algebraic reconstruction technique (S-ART) algorithm and the filtered back projection (FBP) algorithm with the new filter, an efficient and feasible interior reconstruction algorithm is proposed in this paper. The algorithm uses the S-ART algorithm to quickly recover the complete projection data and then uses the new ramp filter which can suppress the high-frequency noise in the projection data to filter the recovered complete projection data. Finally, the interior reconstructed images are obtained by back projection. The computational complexity of the proposed algorithm is close to that of the FBP algorithm for the reconstruction of the whole object, and the reconstructed image quality is acceptable, which provides an effective method for interior reconstruction in CBCT. Simulation results show the effectiveness of the method.

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Funding

This work was supported by the Scientific Research Startup Fund of Nanchang Institute of Science and Technology (Grant No. 20201072), the Nanchang Key Laboratory of Internet of Things Information Visualization Technology (Grant No. 2020-NCZDSY-017), and the Science and Technology Research Project of Jiangxi Province (Grant No. GJJ212503).

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  1. School of Artificial Intelligence, Nanchang Institute of Science and Technology, Nanchang, 330108, China

    Wang Xianchao, Li Shaoyi & Hou Changhui

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  1. Wang Xianchao
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  2. Li Shaoyi
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  3. Hou Changhui
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Correspondence to Wang Xianchao.

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Xianchao, W., Shaoyi, L. & Changhui, H. Interior Reconstruction from Truncated Projection Data in Cone-beam Computed Tomography. J Digit Imaging 36, 250–258 (2023). https://doi.org/10.1007/s10278-022-00695-8

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