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http://dx.doi.org/10.15701/kcgs.2017.23.5.19

Automatic Segmentation of the Mandible using Shape-Constrained Information in Cranio-Maxillo-Facial CBCT Images  

Kim, Joojin (Department of Software Convergence, Seoul Women's University)
Lee, Min Jin (Department of Software Convergence, Seoul Women's University)
Hong, Helen (Department of Software Convergence, Seoul Women's University)
Publication Information
Journal of the Korea Computer Graphics Society / v.23, no.5, 2017 , pp. 19-27 More about this Journal
Abstract
In this paper, we propose an automatic segmentation method of the mandible using shape-constrained information in cranio-maxillo-facial CBCT images. The proposed method consists of the following two steps. First, the mandible segmentation based on the global shape information is performed through the statistical shape model generated using the MDCT images. Second, improvement of mandible segmentation is performed considering the local shape information and intensity characteristics of the mandible. To evaluate the performance of the proposed method, the proposed method was evaluated qualitatively and quantitatively based on the results of manual segmentation by expert. Experimental results show that the Dice Similarity Coefficient of the proposed method was 95.64% and 90.97%, respectively, in the mandible body region including the narrow region of large curvature and the condyle region with large positional variance.
Keywords
cranio-maxillo-facial CBCT image; mandible segmentation; shape-constrained segmentation;
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