• DocumentCode
    2603864
  • Title

    User-guided segmentation for medical image using belief propagation

  • Author

    Chai, YoungJoon ; Park, JinYong ; Kim, Tae-Yong

  • Author_Institution
    Chung-Ang Univ., Seoul, South Korea
  • fYear
    2011
  • fDate
    14-17 June 2011
  • Firstpage
    226
  • Lastpage
    227
  • Abstract
    Medical image processing is considered on an important elements and image segmentation is still a challenging area. Recently, researches for the CT or MRI images are in progress to measure the degree of fatty degeneration; and the size of muscle rupture. However, the segmentation of the medical image is not easy because of irregularity of muscle shape, noises of the MRI or CT image and unclear boundary features. In this paper, we propose a segmentation method using the active contour with the belief Propagation to overcome the local energy minima problem occurred on the Snake or active contour method. Moreover, the proposed method detects the optimum boundary using the semi-automatic method with the user-guided model and it increase the user convenience and computational efficiency.
  • Keywords
    belief networks; biomedical MRI; computerised tomography; image segmentation; medical image processing; CT; MRI; active contour; belief propagation; medical image processing; unclear boundary features; user-guided segmentation; Active contours; Belief propagation; Biomedical imaging; Computational modeling; Image segmentation; Muscles; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics (ISCE), 2011 IEEE 15th International Symposium on
  • Conference_Location
    Singapore
  • ISSN
    0747-668X
  • Print_ISBN
    978-1-61284-843-3
  • Type

    conf

  • DOI
    10.1109/ISCE.2011.5973820
  • Filename
    5973820