DOI QR코드

DOI QR Code

Metal Area Segmentation in X-ray CT Images Using the RNA (Relevant Neighbor Ar ea) Principle

  • Kim, Youngshin (School of Electronic and Electrical Computer Engineering, Sungkyunkwan University) ;
  • Kwon, Hyukjoon (School of Electronic and Electrical Computer Engineering, Sungkyunkwan University) ;
  • Kim, Joongkyu (School of Electronic and Electrical Computer Engineering, Sungkyunkwan University) ;
  • Yi, Juneho (School of Electronic and Electrical Computer Engineering, Sungkyunkwan University)
  • 투고 : 2012.09.16
  • 심사 : 2012.11.13
  • 발행 : 2012.12.31

초록

The problem of Metal Area Segmentation (MAS) in X-ray CT images is a very hard task because of metal artifacts. This research features a practical yet effective method for MAS in X-ray CT images that exploits both projection image and reconstructed image spaces. We employ the Relevant Neighbor Area (RNA) idea [1] originally developed for projection image inpainting in order to create a novel feature in the projection image space that distinctively represents metal and near-metal pixels with opposite signs. In the reconstructed result of the feature image, application of a simple thresholding technique provides accurate segmentation of metal areas due to nice separation of near-metal areas from metal areas in its histogram.

키워드

참고문헌

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