Analysis of dental plaque by using cellular neural network-based image segmentation.
- Author:
Qing-xian LUAN
1
;
Xiao LI
;
Jia-yin KANG
;
Jin-zhu LIU
;
Le-quan MIN
Author Information
- Publication Type:Journal Article
- MeSH: Dental Plaque; diagnosis; Dental Plaque Index; Female; Humans; Image Processing, Computer-Assisted; Male; Neural Networks (Computer); Photography, Dental
- From: Chinese Journal of Stomatology 2007;42(12):720-722
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo establish and evaluate a new method for measurement of dental plaque by using cellular neural network-based image segmentation.
METHODSA 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.
RESULTSThe 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).
CONCLUSIONSCellular neural network-based image segmentation is a new method feasible for evaluating dental plaque.
