Metal artifact reduction in CT by identifying missing data hidden in metals

Hyoung Suk Park, Jae Kyu Choi, Kyung Ran Park, Kyung Sang Kim, Sang Hwy Lee, Jong Chul Ye, Jin Keun Seo

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


There is increasing demand in the field of dental and medical radiography for effective metal artifact reduction (MAR) in computed tomography (CT) because artifact caused by metallic objects causes serious image degradation that obscures information regarding the teeth and/or other biological structures. This paper presents a new MAR method that uses the Laplacian operator to reveal background projection data hidden in regions containing data from metal. In the proposed method, we attempted to decompose the projection data into two parts: data from metal only (metal data), and background data in the absence of metal. Removing metal data from the projections enables us to perform sparsity-driven reconstruction of the metal component and subsequent removal of the metal artifact. The results of clinical experiments demonstrated that the proposed MAR algorithm improves image quality and increases the standard of 3D reconstruction images of the teeth and mandible.

Original languageEnglish
Pages (from-to)357-372
Number of pages16
JournalJournal of X-Ray Science and Technology
Issue number3
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Radiation
  • Instrumentation
  • Radiology Nuclear Medicine and imaging
  • Condensed Matter Physics
  • Electrical and Electronic Engineering


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