Title :
Automatic classification of teeth in bitewing dental images
Author :
Mahoor, Mohammad Hossein ; Abdel-Mottaleb, Mohamed
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
Abstract :
We present an automated algorithm to classify teeth in bitewing dental images, using Bayesian classification, and assign an absolute number to each tooth based on common numbering system used in dentistry. Fourier descriptors of the contours of the molar and the premolar teeth in bitewing images are used in the Bayesian classification of these two types of the teeth. Then, the spatial relation between the two types of the teeth is considered to number each tooth and correct the misclassification of some teeth in order to obtain high precision results. Experiments with 50 bitewing images containing more than 400 teeth show that our method is capable of classifying and assigning absolute index number to the teeth with high accuracy.
Keywords :
Bayes methods; dentistry; diagnostic radiography; image classification; medical image processing; Bayesian classification; Fourier descriptor; automatic classification; bitewing dental image; common numbering system; dentistry; molar contour; premolar teeth; teeth; teeth misclassification; Bayesian methods; Dentistry; Forensics; Image databases; Image segmentation; Information retrieval; Radiography; Shape; Spatial databases; Teeth;
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
Print_ISBN :
0-7803-8554-3
DOI :
10.1109/ICIP.2004.1421863