• DocumentCode
    2759162
  • Title

    A Novel Computerized Method Based on Support Vector Machine for Tongue Diagnosis

  • Author

    Gao, Zhong ; Po, Laiman ; Jiang, Wu ; Zhao, Xin ; Dong, Hao

  • Author_Institution
    Sch. of Telecommun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing
  • fYear
    2007
  • fDate
    16-18 Dec. 2007
  • Firstpage
    849
  • Lastpage
    854
  • Abstract
    The tongue diagnosis is an important diagnostic method in traditional chinese medicine (TCM). In this paper, we present a novel computerized tongue inspection method based on support vector machine (SVM). First, two kinds of quantitative features, chromatic and textural measures, are extracted from tongue images by using popular image processing techniques. Then, support vector machine and Bayesian network are employed to build the mapping relationships between these features and diseases, respectively. Finally, we present a comparison between SVM and BN classification. The experiment results show that we can use SVM to classify the tongue images more excellently and get a relative reliable prediction of diseases based on these features.
  • Keywords
    Bayes methods; feature extraction; image classification; image texture; inspection; medical image processing; support vector machines; Bayesian network; chromatic measure; computerized tongue inspection; image classification; image processing; support vector machine; textural measure; tongue diagnosis; traditional Chinese medicine; Bayesian methods; Biomedical imaging; Diseases; Internet; Medical diagnostic imaging; Pathology; Support vector machine classification; Support vector machines; Telecommunication computing; Tongue; Bayesian networks; computerized tongue diagnosis; support vector machine; traditional Chinese medicine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal-Image Technologies and Internet-Based System, 2007. SITIS '07. Third International IEEE Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3122-9
  • Type

    conf

  • DOI
    10.1109/SITIS.2007.115
  • Filename
    4618862