title: [Analysis of dental plaque by using cellular neural network-based image segmentation].
abstract: 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.
authors.affiliation: School of Information Engineering and School of Applied Scinces, University of Science and Technology, Beijing 100083, China.
authors.forename: Qing-xian
authors.initials: QX
authors.lastname: Luan
authors.forename: Xiao
authors.initials: X
authors.lastname: Li
authors.forename: Jia-yin
authors.initials: JY
authors.lastname: Kang
authors.forename: Jin-zhu
authors.initials: JZ
authors.lastname: Liu
authors.forename: Le-quan
authors.initials: LQ
authors.lastname: Min
mesh_terms: D003773:Dental Plaque / Q000175:diagnosis*; D003774:Dental Plaque Index; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D016571:Neural Networks, Computer; D023861:Photography, Dental