• DocumentCode
    545272
  • Title

    Hierarchical decision tree for the classification of prostate tissue

  • Author

    Huynen, A.L. ; Giesen, R.J.B. ; Laduc, R. ; Debruyne, F.M.J. ; Wijkstra, H.

  • Author_Institution
    BioMedical Engineering, Dept. of Urology, University Hospital Nijmegen PO Box 9101, 6500 HB NIJMEGEN, the Netherlands
  • Volume
    5
  • fYear
    1992
  • fDate
    Oct. 29 1992-Nov. 1 1992
  • Firstpage
    2100
  • Lastpage
    2101
  • Abstract
    This paper describes an algorithm for the classification of texture in ultrasonographic prostate images. The texture is described by parameters which have to be correlated to the histology of the tissue in the image. An adaptive learn algorithm is used to build a hierarchical decision tree for the partitioning of the parameter space. This tree is then used to predict the probability of malignancy in the tissue.
  • Keywords
    Sensitivity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1992 14th Annual International Conference of the IEEE
  • Conference_Location
    Paris, France
  • Print_ISBN
    0-7803-0785-2
  • Electronic_ISBN
    0-7803-0816-6
  • Type

    conf

  • DOI
    10.1109/IEMBS.1992.5762186
  • Filename
    5762186
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=545272