• DocumentCode
    3320666
  • Title

    A new method for image segmentation based on fuzzy knowledge

  • Author

    Tresp, Christopher ; Jagar, M. ; Moser, Michael ; Hiltner, Jens ; Fathi, Madjid

  • Author_Institution
    Aachen Univ. of Technol., Germany
  • fYear
    1996
  • fDate
    4-5 Nov 1996
  • Firstpage
    227
  • Lastpage
    233
  • Abstract
    Within this work a method for knowledge based fuzzy image segmentation is introduced. The basic idea comes from the field of automated medical MRI segmentation where the well-known standard methods have proven insufficient to solve the task. Therefore, a method especially for the problems concerning vagueness in medical imaging has been developed. Beside the improved segmentation procedures, the development has a general impact on the conventional model of image analysis
  • Keywords
    biomedical NMR; fuzzy set theory; image segmentation; medical image processing; automated medical MRI segmentation; image analysis model; knowledge-based fuzzy image segmentation; magnetic resonance imaging; medical diagnostic imaging; vagueness; Biomedical imaging; Brain modeling; Computer science; Concrete; Fuzzy systems; Head; Humans; Image analysis; Image segmentation; Magnetic resonance imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Systems, 1996., IEEE International Joint Symposia on
  • Conference_Location
    Rockville, MD
  • Print_ISBN
    0-8186-7728-7
  • Type

    conf

  • DOI
    10.1109/IJSIS.1996.565073
  • Filename
    565073