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Erschienen in: Journal of Digital Imaging 1/2023

29.08.2022 | Original Paper

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

verfasst von: Wang Xianchao, Li Shaoyi, Hou Changhui

Erschienen in: Journal of Imaging Informatics in Medicine | Ausgabe 1/2023

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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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Metadaten
Titel
Interior Reconstruction from Truncated Projection Data in Cone-beam Computed Tomography
verfasst von
Wang Xianchao
Li Shaoyi
Hou Changhui
Publikationsdatum
29.08.2022
Verlag
Springer International Publishing
Erschienen in
Journal of Imaging Informatics in Medicine / Ausgabe 1/2023
Print ISSN: 2948-2925
Elektronische ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-022-00695-8

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