Paper Info
Title
High-kVp Assisted Metal Artifact Reduction for X-Ray Computed Tomography.
Abstract
In X-ray computed tomography (CT), the presence of metallic parts in patients causes serious artifacts and degrades image quality. Many algorithms were published for metal artifact reduction (MAR) over the past decades with various degrees of success but without a perfect solution. Some MAR algorithms are based on the assumption that metal artifacts are due only to strong beam hardening and may fail in the case of serious photon starvation. Iterative methods handle photon starvation by discarding or underweighting corrupted data, but the results are not always stable and they come with high computational cost. In this paper, we propose a high-kVp-assisted CT scan mode combining a standard CT scan with a few projection views at a high-kVp value to obtain critical projection information near the metal parts. This method only requires minor hardware modifications on a modern CT scanner. Two MAR algorithms are proposed: dual-energy normalized MAR (DNMAR) and high-energy embedded MAR (HEMAR), aiming at situations without and with photon starvation respectively. Simulation results obtained with the CT simulator CatSim demonstrate that the proposed DNMAR and HEMAR methods can eliminate metal artifacts effectively.
Year
DOI
Venue
2016
10.1109/ACCESS.2016.2602854
IEEE ACCESS
Keywords
Field
DocType
Computed tomography,metal artifact reduction,kVp switching,iterative reconstruction
Iterative reconstruction,Photon,Metal Artifact,Computer vision,X-ray,Normalization (statistics),Computer science,Iterative method,Image quality,Artificial intelligence,Scanner
Journal
Volume
ISSN
Citations 
4
2169-3536
1
PageRank 
References 
Authors
0.37
6
4
Name
Order
Citations
PageRank
Yan Xi1133.02
Yannan Jin271.27
Bruno De Man3638.41
Ge Wang41000142.51