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Individual tooth segmentation from CT images using level set method with shape and intensity prior

机译:使用形状和强度先验的水平集方法从CT图像中进行单个牙齿分割

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摘要

3D visualization of teeth from CT images provides important assistance for dentists performing orthodontic surgery and treatment. However, dental CT images present several major challenges for the segmentation of tooth, which touches with adjacent teeth as well as surrounding periodontium and jaw bones. Moreover, tooth contour suffers from topological changes and splits into several branches. In this work, we focus on the segmentation of individual teeth with complete crown and root parts. To this end, we propose adaptive active contour tracking algorithms: single level set method tracking for root segmentation to handle the complex image conditions as well as the root branching problem, and coupled level set method tracking for crown segmentation in order to separate the touching teeth and create the virtual common boundaries between them. Furthermore, we improve the variational level set method in several aspects: gradient direction is introduced into the level set framework to prevent catching the surrounding object boundaries; in addition to the shape prior, intensity prior is introduced to provide adaptive shrinking or expanding forces in order to deal with the topological changes. The test results for both tooth segmentation and 3D reconstruction show that the proposed method can visualize individual teeth with high accuracy and efficiency.
机译:通过CT图像对牙齿进行3D可视化,为牙医进行正畸手术和治疗提供了重要的帮助。但是,牙科CT图像对牙齿的分割提出了几个主要挑战,该牙齿与相邻牙齿以及周围的牙周和颌骨接触。此外,牙齿轮廓受到拓扑变化的影响并且分裂成几个分支。在这项工作中,我们专注于完整冠和根部分的单个牙齿的分割。为此,我们提出了自适应主动轮廓跟踪算法:针对牙根分割的单水平集方法跟踪以处理复杂的图像条件以及牙根分支问题;针对牙冠分割的耦合水平集方法跟踪以分离触摸牙齿并在它们之间创建虚拟的公共边界。此外,我们在几个方面改进了变分水平集方法:将梯度方向引入水平集框架以防止捕获周围的对象边界;除了形状先验之外,还引入了强度先验以提供自适应的收缩力或扩张力,以应对拓扑变化。牙齿分割和3D重建的测试结果表明,该方法能够以较高的准确性和效率可视化单个牙齿。

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