• DocumentCode
    1964408
  • Title

    Using deformable models to segment complex structures under geometric constraints

  • Author

    Gout, Christian ; Vieira-Teste, Sylvie

  • Author_Institution
    Dept. de Math. Appl., Pau Univ., France
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    101
  • Lastpage
    105
  • Abstract
    In many problems of medical or geophysical interest, when trying to segment an image, one has to deal with data that exhibit very complex structures. This problem occurs when images have discontinuities: in medical imaging (fractures radiography), in geophysics (segmentation of a set of layers and faults) etc. To solve this problem, we present a segmentation method which uses deformable models. The originality of the method is that we have interpolation data and triple points that involves making some geometric constraints on the model. We also propose a method for noise removal because it is well known that most of these images are noisy, that could hinder the segmentation. Numerical results on geophysical images are given
  • Keywords
    computational geometry; data structures; geophysical signal processing; image segmentation; interpolation; medical image processing; complex data structures; deformable models; geometric constraints; geophysical image; image discontinuities; image segmentation; interpolation data; medical image; noisy images; triple points; Active contours; Arthritis; Deformable models; Image segmentation; Independent component analysis; Integrated circuit noise; Level set; Minimization methods; Shape; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Interpretation, 2000. Proceedings. 4th IEEE Southwest Symposium
  • Conference_Location
    Austin, TX
  • Print_ISBN
    0-7695-0595-3
  • Type

    conf

  • DOI
    10.1109/IAI.2000.839580
  • Filename
    839580