• DocumentCode
    1928891
  • Title

    Clinical X-Ray Image Based Tooth Decay Diagnosis using SVM

  • Author

    Li, Wei ; Kuang, Wei ; Li, Yun ; Li, Yu-jing ; Ye, Wei-ping

  • Author_Institution
    Beijing Normal Univ., Beijing
  • Volume
    3
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    1616
  • Lastpage
    1619
  • Abstract
    Automatic tooth decay diagnosis achieved the satisfying results on the extracted tooth diagnosis by rule-based system and Artificial Neural Network (ANN). This paper, focusing on clinical tooth decay detection, introduces a Support Vector Machine (SVM) based diagnosis method. For comparison, an additional back propagation neural network (BPNN) tooth decay diagnosis experiment is reported. Comparative results indicate that SVM based method gives better performance than the one BPNN based.
  • Keywords
    backpropagation; image processing; neural nets; support vector machines; artificial neural network; back propagation neural network; clinical x-ray image; support vector machine; tooth decay diagnosis; Artificial neural networks; Cybernetics; Dentistry; Feature extraction; Image analysis; Machine learning; Support vector machine classification; Support vector machines; Teeth; X-ray imaging; BPNN; Clinical X-ray image; SVM; Tooth decay diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370404
  • Filename
    4370404