形状特征引导的下牙槽神经管重建  

Reconstruction of Inferior Alveolar Nerve Canal Based on Shape Feature

作　　者：侯小叶[1] 杨玲[1] 王中科[2] 杨智鹏[1] 

机构地区：[1]成都信息工程学院电子工程学院,成都610225 [2]成都信息工程学院网络工程学院,成都610225

出　　处：《生物医学工程学杂志》2014年第2期327-331,共5页Journal of Biomedical Engineering

摘　　要：下牙槽神经(IAN)X影像相对其周围组织影像异常模糊,且CT值远小于颌骨的CT值,直接对其重建难于达到透视效果,传统临床上依靠医生手动绘制,带有强烈的主观性。本文提出一种基于形状特征的IAN管分区重建方法。根据IAN管的解剖特征将其分为三部分分别进行处理,在下颌升支处,直接利用局部信息约束的形状导向水平集算法对其分割;对下颌骨体部,利用空间B样条曲线拟合出其中心走向,然后沿曲线的切向建立IAN管切面;对颏孔区,采用自适应阈值Canny算法提取边缘寻找其中心曲线,同样沿其切向建立IAN管的切面,最后用形象化工具包(VTK)对上述数据进行重建IAN管。在用VTK重建IAN管时,通过对不同组织的CT值设定不同的不透明度和颜色值,可以清晰的达到IAN管的透视显示。用本文方法重建的IAN管的空间走向较直接对分割结果进行重建的效果平滑,颏孔区的形状与解剖结构类似,为临床IAN管的空间定位提供了一种有效的方法。It is difficult to distinguish the inferior alveolar nerve （IAN） from other tissues inside the IAN canal due to their similar CT values in the X image which are smaller than that of the bones. The direct reconstruction, therefore, is difficult to achieve the effects. The traditional clinical treatments mainly rely on doctors＇ manually drawing the X images so that some subjective results could not be avoided. This paper proposes the partition reconstruction of IAN canal based on shape features. According to the anatomical features of the IAN canal, we divided the image into three parts and treated the three parts differently. For the first, the directly part of the mandibular, we used Shape-driven Level-set Algorithm Restrained by Local Information （BSLARLI） segment IAN canal. For the second part, the man- dibular body, we used Space B-spline curve fitting IAN canal＇s center, then along the center curve established the cross section. And for the third part, the mental foramen, we used an adaptive threshold Canny algorithm to extract IAN canal＇s edge to find center curve, and then along it established the cross section similarly. Finally we used the Visualization Toolkit （VTK） to reconstruct the CT data as mentioned above. The VTK reconstruction result by set- ting a different opacity and color values of tissues CT data can perspectively display the INA canal clearly. The re- construction result by using this method is smoother than that using the segmentation results and the anatomical structure of mental foramen position is similar to the real tissues, so it provides an effective method for locating the spatial position of the IAN canal for implant surgeries.

关 键 词：下牙槽神经管 CT 空间B样条曲线 自适应阈值Canny算法 VTK重建 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]