Sparse Angle CBCT Reconstruction Based on Guided Image Filtering

Cone-beam Computerized Tomography (CBCT) has the advantages of high ray utilization and detection efficiency, short scan time, high spatial and isotropic resolution. However, the X-rays emitted by CBCT examination are harmful to the human body, so reducing the radiation dose without damaging the rec...

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Bibliographic Details
Main Authors: Siyuan Xu, Bo Yang, Congcong Xu, Jiawei Tian, Yan Liu, Lirong Yin, Shan Liu, Wenfeng Zheng, Chao Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Oncology
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Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.832037/full
Description
Summary:Cone-beam Computerized Tomography (CBCT) has the advantages of high ray utilization and detection efficiency, short scan time, high spatial and isotropic resolution. However, the X-rays emitted by CBCT examination are harmful to the human body, so reducing the radiation dose without damaging the reconstruction quality is the key to the reconstruction of CBCT. In this paper, we propose a sparse angle CBCT reconstruction algorithm based on Guided Image FilteringGIF, which combines the classic Simultaneous Algebra Reconstruction Technique(SART) and the Total p-Variation (TpV) minimization. Due to the good edge-preserving ability of SART and noise suppression ability of TpV minimization, the proposed method can suppress noise and artifacts while preserving edge and texture information in reconstructed images. Experimental results based on simulated and real-measured CBCT datasets show the advantages of the proposed method.
ISSN:2234-943X