水平集活动轮廓模型的3维牙齿重建

目的 建立患者口腔每颗牙齿独立的3维模型对于计算机口腔修复的精确定位和量化评估具有十分重要的意义。针对口腔CT图像序列的牙齿形态变化和排列特点，提出一种新颖的基于水平集活动轮廓模型的3维牙齿重建方法。方法 基于层间映射机制，对不同部位牙层切片采用不同的分割模型：利用先验形状约束能量、基于Flux模型的边缘梯度能量、基于先验灰度的局部区域能量相结合构造的单相混合水平集模型分割牙根层切片轮廓；利用结合区域竞争约束的双相混合水平集模型分割牙冠层切片轮廓；最后利用这些层间轮廓重建出牙齿3维模型。结果 对不同位置的牙齿CT图像进行分割实验，结果表明，与现有的方法相比，本文方法具有较好的分割效果和较高的准确率，平均分割相似系数达到96%。结论 本文的混合水平集模型能有效克服牙髓腔和牙槽骨的干扰以及图像灰度不均匀等问题，较准确地重建出每颗牙齿独立的3维模型，从而为制定口腔修复规划、生物力学分析等奠定坚实的基础。

Three dimention tooth reconstruction using level set active contour model

Objective Building individual 3D dental models for patients is critical for the accurate localization and quantitative evaluation of computer dental restoration. A novel 3D tooth reconstruction method based on level set active contour model is proposed for the characteristics of teeth morphologic change and permutation of oral CT image sequences. Method Different models are adopted for different parts of tooth slices in the mapping mechanism between layers. A single hybrid level set model combined with the prior shape constraint energy, the edge gradient energy based on flux model, and the local region energy based on prior intensity is used to segment tooth contour in dental root slices; while a double hybrid level set model combined with regional competitive restraint energy is used for dental crown slices. These segmented contours are then applied to reconstruct 3D dental models. Result After testing numerous CT tooth slices at different positions, the results demonstrate that the proposed method provides better segmentation outcome and higher percentage accuracy than existing methods. The mean similarity index can reach 96%. Conclusion The proposed hybrid level set model can efficiently overcome the interference of pulp cavity and alveolar bone as well as the problem of uneven intensity. Furthermore, the method can create a relatively accurate reconstruction of the 3D models for each individual tooth, which can lay a solid foundation for dental restoration planning and biomechanical analysis.