Open AccessMulti-pass approach to reduce cone-beam artifacts in a circular orbit cone-beam CT system
Author(s) -
Chulhee Han,
Jongduk Baek
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.010108
Subject(s) - imaging phantom , cone beam computed tomography , reduction (mathematics) , beam (structure) , cone beam ct , optics , iterative reconstruction , detector , image quality , circular orbit , orbit (dynamics) , artifact (error) , projection (relational algebra) , computer science , mathematics , physics , computer vision , algorithm , computed tomography , image (mathematics) , geometry , medicine , engineering , classical mechanics , radiology , aerospace engineering
We propose a multi-pass approach to reduce cone-beam artifacts in a circular orbit cone-beam computed tomography (CT) system. Employing a large 2D detector array reduces the scan time but produces cone-beam artifacts in the Feldkamp, Davis, and Kress (FDK) reconstruction because of insufficient sampling for exact reconstruction. While the two-pass algorithm proposed by Hsieh is effective at reducing cone-beam artifacts, the correction performance is degraded when the bone density is moderate and the cone angle is large. In this work, we treated the cone-beam artifacts generated from bone and soft tissue as if they were from less dense bone objects and corrected them iteratively. The proposed method was validated using a numerical Defrise phantom, XCAT phantom data, and experimental data from a pediatric phantom followed by image quality assessment for FDK, the two-pass algorithm, the proposed method, and the total variation minimization-based iterative reconstruction (TV-IR). The results show that the proposed method was superior to the two-pass algorithm in cone-beam artifact reduction and effectively reduced the overcorrection by the two-pass algorithm near bone regions. It can also be observed that the proposed method produced better correction performance with fewer iterations than the TV-IR algorithm. A qualitative evaluation with mean-squared error, structural similarity, and structural dissimilarity demonstrated the effectiveness of the proposed method.