摘要
提出一个快速稳定的神经管提取方法,该方法首先通过连通区域的划分和特征分析,检测位于各个剖面图像上的神经管中心点位置;随后通过对检测到的中心点进行样条插值处理,得到神经管中心线;最后通过判断并结合中心线邻近区域内具有相似特征的其他体素点,提取出整个下齿槽神经管.临床获取的齿科CT数据评估结果表明该方法能够成功提取出评估数据中的全部神经管,并且具有很高的精确度.
A robust and fast method was proposed to extract the inferior alveolar nerve (IAN) canals. First of all, the center points of an IAN canal on a series of cross-sectional images were identified by the division and the feature analysis of the connected regions on these images. Then, the centerline of this IAN canal was computed by using a spline interpolation. Finally, the IAN canal was extracted by adding the voxels with similar characteristics to the centerline region. The real dental CT images evaluation results showed that based on the proposed method all the IAN canals in the evaluation datasets could be successfully extracted with high accuracy.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2012年第10期1500-1503,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61071213)
关键词
下齿槽神经管
计算机断层摄影
齿移植手术
剖面图像
特征分析
inferior alveolar nerve canal
computed tomography
dental implant surgery
cross- sectional image
feature analysis