Analysis of dental plaque by using cellular neural network-based image segmentation / 中华口腔医学杂志

ABSTRACT

<p><b>OBJECTIVE</b>To establish and evaluate a new method for measurement of dental plaque by using cellular neural network-based image segmentation.</p><p><b>METHODS</b>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.</p><p><b>RESULTS</b>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).</p><p><b>CONCLUSIONS</b>Cellular neural network-based image segmentation is a new method feasible for evaluating dental plaque.</p>