• DocumentCode
    578859
  • Title

    Segmentation of MR images using multispectral fusion approach : A study and an evaluation

  • Author

    Chaabane, Lamiche ; Abdelouahab, Moussaoui

  • Author_Institution
    Dept. of Comput. Sci., Univ. of M´´sila, M´´sila, Algeria
  • fYear
    2012
  • fDate
    1-3 July 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some possibility theory concepts. Information provided by different sources of MR images is extracted and modeled separately in each one using MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm, extracted data obtained are combined with an operator which can managing the uncertainty and ambiguity in the images and the final segmented image is constructed in decision step. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR Images.
  • Keywords
    biomedical MRI; feature extraction; fuzzy set theory; image fusion; image segmentation; medical image processing; possibility theory; MPFCM algorithm; MR image segmenttaion; MR image simulation; data extraction; decision step; magnetic resonance imaging; modified possibilistic fuzzy c-means algorithm; multispectral fusion approach; possibility theory concepts; unsupervised segmentation technique based aggregation approach; Biomedical imaging; Brain modeling; Image segmentation; Magnetic resonance imaging; Possibility theory; MPFCM; MR images; aggregation; possibility theory; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education and e-Learning Innovations (ICEELI), 2012 International Conference on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4673-2226-3
  • Type

    conf

  • DOI
    10.1109/ICEELI.2012.6360567
  • Filename
    6360567