摘要
目的采用细胞神经网络图像分割技术,建立分析牙菌斑的新方法并对其进行评价。方法从北京市高血压联盟在首钢系统体检的人群中筛选195名个体,菌斑染色后,用 Olympus 数码照相机拍摄口内前牙区的数码像,同时评价前牙区的 Turesky 菌斑指数。采用细胞神经网络图像分割技术完成图像分析。结果不同操作者的剪切引起分析结果的偏差很小。Kappa 值为0.935,两名操作者前牙唇面牙菌斑覆盖牙表面积的百分比(P%)的 Pearson 相关系数为0.988(P<0.001)。用图像法测量菌斑的百分比与传统的菌斑指数间有较高的相关一致性,Pearson 相关系数为0.853(P<0.001)。结论细胞神经网络图像分割技术是评价牙菌斑的一种可行的新方法。
Objective To establish and evaluate a new method for measurement of dental plaque by using cellular neural network-based image segmentation. Methods A total of 195 subjects were selected from community population. After dental plaque staining, oral digital picture of anterior teeth area was taken by an Olympus digital camera（ C-7070 Wide Zoom）. At the same time, the Turesky dental plaque indices of anterior teeth were evaluated. The image analysis was conducted by cellular neural network-based image segmentation. Results The image cutting errors between two operators were very small. The Kappa value is 0. 935. Pearson＇ s correlation coefficient is 0. 988 （ P 〈 0. 001 ） . There was high correlative consistency between traditional dental plaque index and plaque percentage obtained by using image analysis. Pearson＇s correlation coefficient was 0. 853 （ P 〈 0. 001 ） . Conclusions Cellular neural network-based image segmentation is a new method feasible for evaluating dental plaque.
出处
《中华口腔医学杂志》
CAS
CSCD
北大核心
2007年第12期720-722,共3页
Chinese Journal of Stomatology
基金
国家自然科学基金(60674059)
首都医学发展科研基金(2003-2005)
