• DocumentCode
    1566495
  • Title

    A Hierarchical Topological Knowledge Based Image Segmentation Approach Optimizing the use of Contextual Regions of Interest : Illustration for Medical Image Analysis

  • Author

    Fasquel, J. -B. ; Agnus, V. ; Soler, Luciana ; Marescaux, J.

  • Author_Institution
    IRCAD, Strasbourg, France
  • fYear
    2006
  • Firstpage
    777
  • Lastpage
    780
  • Abstract
    This paper concerns image segmentation and presents a method to automically determine optimal regions of interest (ROI) according to topological information. The use of ROI avoids the processing of irrelevant image points, therefore improving and accelerating segmentations. ROI determination is based on the optimal use of both the a priori knowledge about topological structure of an image and the contextual information. Contextual information concerns the nature of already segmented regions in the case of the hierarchical segmentation approach we consider. We describe this general purpose method and propose a formulation for the optimal determination of ROIs according to both informations. Then, we illustrate the use and the implementation of such a method in the particular case of medical image segmentation.
  • Keywords
    image segmentation; medical image processing; ROI; contextual information; image segmentation; medical image analysis; regions of interest; topological information; topological knowledge; Acceleration; Biomedical image processing; Biomedical imaging; Data mining; Histograms; Image analysis; Image segmentation; Interactive systems; Photometry; Topology; Biomedical image processing; Image segmentation; Interactive systems; Knowledge based systems; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.312517
  • Filename
    4106645