Automated Detection and Quantification of Early Caries Lesions on Images Captured by Intraoral Camera
In recent years, quantifying the severity of early caries lesions based on white light and/or fluorescence images captured by intraoral camera has been becoming a hot spot in caries research field. In order to quantify the severity of the early caries lesions, it needs to detect and segment the caries lesions accurately first. However, to date, the published methods are mainly based on threshold techniques, and it is difficult to obtain desirable results because the intensity of the teeth changes significantly. To solve this problem, this paper presents an automated detection and quantification algorithm by using a morphological top-hat/bottom-hat method along with a multi-resolution surface reconstruction technique, which is based on local intensity and morphological characteristics of caries images captured by the intraoral oral camera, for early caries lesions. The preliminary experimental results on ex vivo data demonstrated the potential of the proposed algorithm.
Jiayong Yan Yongjia Xiang Xiaohua Jian
Suzhou Institute of Biomedical Engineering and Technology, Suzhou, 215263, P.R. China
国际会议
2011 International Symposium on Bioelectronics and Bioinformatics(第二届国际生物医学电子学与生物信息学学术会议 ISBB 2011)
苏州
英文
251-254
2011-11-03（万方平台首次上网日期，不代表论文的发表时间）