대한의용생체공학회:의공학회지 (Journal of Biomedical Engineering Research)

  • 제28권6호
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  • Pages.713-720
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  • 2007
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  • 1229-0807(pISSN)
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  • 2288-9396(eISSN)
대한의용생체공학회 (The Korean Society of Medical and Biological Engineering)
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Automatic Bone Segmentation from CT Images Using Chan-Vese Multiphase Active Contour

  • Truc, P.T.H. (Department of Computer Engineering, Kyung Hee University) ;
  • Kim, T.S. (Department of Biomedical Engineering, Kyung Hee University) ;
  • Kim, Y.H. (College of Advanced Technology, Kyung Hee University) ;
  • Ahn, Y.B. (Department of Electronic Engineering, Konkuk University) ;
  • Lee, Y.K. (Department of Computer Engineering, Kyung Hee University) ;
  • Lee, S.Y. (Department of Computer Engineering, Kyung Hee University)
  • 발행 : 2007.12.31
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초록

In image-guided surgery, automatic bone segmentation of Computed Tomography (CT) images is an important but challenging step. Previous attempts include intensity-, edge-, region-, and deformable curve-based approaches [1], but none claims fully satisfactory performance. Although active contour (AC) techniques possess many excellent characteristics, their applications in CT image segmentation have not worthily exploited yet. In this study, we have evaluated the automaticity and performance of the model of Chan-Vese Multiphase AC Without Edges towards knee bone segmentation from CT images. This model is suitable because it is initialization-insensitive and topology-adaptive. Its segmentation results have been qualitatively compared with those from four other widely used AC models: namely Gradient Vector Flow (GVF) AC, Geometric AC, Geodesic AC, and GVF Fast Geometric AC. To quantitatively evaluate its performance, the results from a commercial software and a medical expert have been used. The evaluation results show that the Chan-Vese model provides superior performance with least user interaction, proving its suitability for automatic bone segmentation from CT images.

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참고문헌

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