• DocumentCode
    1987077
  • Title

    A Kind of Computer Microscopic Urinary Sediments Analyzer by SVM

  • Author

    Liu, XueMei ; Sun, ZhiJian

  • Author_Institution
    Adm. of State-Owned Assets, Qingdao Technol. Univ., Qingdao
  • Volume
    1
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    483
  • Lastpage
    486
  • Abstract
    Urinary sediment inspecting is that doctor counts the organic visible sediments in urinary and different sediments components so that we can know the status of kidney disease. In this system, we adopt the digital image microscope technology to observe directly the visible components which include RBC, WBC, Cast, Crystal etc in urinary sediment. The proposed method which uses the computer image recognition and SVM technology carries out automatically sampling image and analyzing and diagnosis the diseases. Moreover, it not only alleviates the doctors´ workload and avoids omission or repetitive counting, but also improves the accuracy of counting and is convenience to saving and processing image and others the guarantee for the following analysis and summary.
  • Keywords
    biomedical equipment; computerised instrumentation; diseases; image recognition; image sampling; medical computing; microscopes; support vector machines; SVM; computer image recognition; computer microscopic urinary sediments analyzer; digital image microscope technology; image sampling; kidney disease; support vector machines; urinary sediment; Digital images; Diseases; Educational technology; Image analysis; Image processing; Image recognition; Microscopy; Sediments; Support vector machine classification; Support vector machines; Support Vector Machine (SVM); Urinary sediment; digital image microscope technology; image processing algorithms; multi-classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3563-0
  • Type

    conf

  • DOI
    10.1109/ETTandGRS.2008.235
  • Filename
    5070201