• DocumentCode
    165946
  • Title

    Fuzzy algorithm for segmentation of images in extraction of objects from MRI

  • Author

    Kubicek, Jan ; Penhaker, Marek

  • Author_Institution
    Dept. of Cybern. & Biomed. Eng., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
  • fYear
    2014
  • fDate
    24-27 Sept. 2014
  • Firstpage
    1422
  • Lastpage
    1427
  • Abstract
    The paper discusses a suitable segmentation method for extraction of specific objects from Magnetic Resonance Imaging (MRI). A particular attention is paid to detection and extraction of articular tissues from knee images. This is a pressing issue for physicians because MRI reveals often damage to articular cartilage which is shown by a minor change in a brightness scale. The image segmentation can provide a detailed colour map which shows distribution of the tissue densities. This algorithm is based on detection of local extremes in histogram and uses a membership function in order to allocate each image density into an output set. Each such set is given a colour from a predefined colour spectrum. This procedure can easily differentiate between the tissue structures based on the tissue densities.
  • Keywords
    biological tissues; biomedical MRI; fuzzy set theory; image colour analysis; image segmentation; medical image processing; MRI; articular cartilage; articular tissues; brightness scale; colour map; colour spectrum; fuzzy algorithm; image density; image segmentation; knee images; magnetic resonance imaging; membership function; physicians; segmentation method; tissue density; tissue structures; Algorithm design and analysis; Histograms; Image color analysis; Image segmentation; Interpolation; Magnetic resonance imaging; Pathology; MATLAB; fuzzy logics; image histogram; image segmentation; object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on
  • Conference_Location
    New Delhi
  • Print_ISBN
    978-1-4799-3078-4
  • Type

    conf

  • DOI
    10.1109/ICACCI.2014.6968264
  • Filename
    6968264