• DocumentCode
    3402260
  • Title

    Classification of Urinary Sediments Image Based on Bayesian Classifier

  • Author

    Dong, Liyan ; Yuan, Senmiao ; Liu, Guangyuan ; Zhou, Lingyan ; Li, Yongli

  • Author_Institution
    Jilin Univ., Changchun
  • fYear
    2007
  • fDate
    5-8 Aug. 2007
  • Firstpage
    556
  • Lastpage
    560
  • Abstract
    In this paper a new method of classification of image in medical domain was introduced. Since the traditional way of diagnosis is slow, time-consuming and heavy-workload, the result is largely influenced by the experience of doctor. The new way of classification can largely improve the efficiency and accuracy in diagnosis. The method is based on Naive Bayesian classification. After distinguishing the visible compositions, feature extraction and feature selection, we can get a naive Bayesian classifier which can be used in classifying of object entities. Experiments show that the new method is suitable for image classification.
  • Keywords
    belief networks; feature extraction; image classification; sediments; Bayesian classifier; feature extraction; feature selection; image classification; naive Bayesian classification; object entities; urinary sediments; Automation; Bayesian methods; Biomedical imaging; Data mining; Educational institutions; Feature extraction; Image classification; Mechatronics; Medical diagnostic imaging; Sediments; Bayesian classifier; feature extraction; feature selection; image classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation, 2007. ICMA 2007. International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-0828-3
  • Electronic_ISBN
    978-1-4244-0828-3
  • Type

    conf

  • DOI
    10.1109/ICMA.2007.4303603
  • Filename
    4303603