Quantitative Segmentation and Measurement of Tooth from Computed Tomography Image Based on Regional Adaptive Deformation Model

Lixin Wang, Xinxin Liu, Xiyun Liu, Zhihai Yang, Jian Yang, Danni Ai, Yongtian Wang

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

For tooth segmentation problem on the three-dimensional computed tomography(CT)volume data,this paper proposes a regional adaptive deformable model for tooth structure measurement of CT images.The proposed method combines the automatic thresholding segmentation,CV active contour model,and graph-cut.Firstly,we achieved the segmentation and location of dental crowns by automatic thresholding segmentation.And then by using the above segmentation result as the initial contour,we utilized active contour method to slice gradually the segment of remaining tooth.By incorporating active contour and graph-cut then,we realized the accurate segmentation for tooth root,which is the most difficult to be segmented.The experimental results showed that the proposed tooth structure measurement accurately and automatically segmented dental crowns from CT data,and then rapidly and accurately segmented the tooth neck and tooth root.The structure of tooth could be effectively segmented from CT data by using the proposed method.Experimental results indicated that the proposed method was rather robust and accurate,and could effectively assist the doctor for diagnosis in clinical treatment.

源语言英语
页(从-至)308-314
页数7
期刊Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering
33
2
出版状态已出版 - 1 4月 2016

指纹

探究 'Quantitative Segmentation and Measurement of Tooth from Computed Tomography Image Based on Regional Adaptive Deformation Model' 的科研主题。它们共同构成独一无二的指纹。

引用此