Affiliations: Bio Imaging and Signal Processing Lab., Department Bio
and Brain Engineering, Korea Advanced Institute of Science and Technology
(KAIST), Yuseong-gu, Daejon, Korea | Samsung Medison Co., Ltd., Gangnam-gu, Seoul,
Korea | Department of Information and Communication
Engineering, Chungnam National University, Yuseong-Gu, Daejeon, Korea
Note: [] Corresponding author: Jong Chul Ye, Ph.D., Associate Professor,
Dept. of Bio and Brain Engineering, Korea Advanced Institute of Science and
Technology (KAIST), 335 Gwahak-ro, Yuseong-gu, Daejon 305-701, Korea. Tel.: +82
42 350 4320; Fax: +82 42 350 4310; E-mail: jong.ye@kaist.ac.kr
Abstract: Metal artifact removal (MAR) is one of the most important issues in
x-ray CT reconstruction. Various methods have been suggested for metal artifact
removal, among which projection modification and iterative methods are most
popular. While those methods mainly focus on removing background artifacts, for
some applications such as dental CT the correct reconstruction of metallic
inserts is also important. For this application, we formulate the MAR problem
as a sparse recovery problem since metallic inserts usually occupy very little
volume within a field of view. One of the main advantages of this approach is
to overcome the inconsistency of sinograms from metal artifacts by imposing a
geometric constraint, "sparsity". As a side product of this formulation, a
significant reduction of the sample views is feasible for metal part
reconstruction without sacrificing quality, thanks to the compressed sensing
theory, which minimizes the additional computational overhead. Numerical
results confirm that metallic inserts can be accurately reconstructed with a
significant reduction of computation time.
Keywords: Metal artifact removal, compressed sensing, dental X-ray CT, sparsity
