• DocumentCode
    2692892
  • Title

    Artificial intelligence approaches for cytological image interpretation

  • Author

    Benjamins, V.R. ; Albuquerque, A.R.P.L.

  • Author_Institution
    Lab. of Integrated Syst., Sao Paulo Univ., Brazil
  • Volume
    3
  • fYear
    1994
  • fDate
    2-5 Oct 1994
  • Firstpage
    2306
  • Abstract
    Pathology deals with the recognition of diseases by inspection of cell tissue through a microscope. Providing automated support to pathologists involves two tasks to be solved. First, optical images, provided by an optical microscope, have to be interpreted to decide on the relevant cell characteristics. Secondly, the relevant information is used for disease recognition or identification. In this article we discuss some artificial intelligence approaches relevant for these problems
  • Keywords
    biological techniques; biology computing; cellular biophysics; image recognition; knowledge based systems; medical image processing; optical microscopy; AI; artificial intelligence approaches; cell tissue inspection; cytological image interpretation; disease identification; disease recognition; optical microscope; pathology; Artificial intelligence; Diagnostic expert systems; Diseases; Image color analysis; Information analysis; Inspection; Large scale integration; Microscopy; Pathology; Personal communication networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • Print_ISBN
    0-7803-2129-4
  • Type

    conf

  • DOI
    10.1109/ICSMC.1994.400209
  • Filename
    400209