• DocumentCode
    1787363
  • Title

    An MRF Model for Biomedical Image Segmentation

  • Author

    Daekeun You ; Antani, Sameer ; Demner-Fushman, Dina ; Thoma, George R.

  • Author_Institution
    Nat. Libr. of Med., Nat. Inst. of Health, Bethesda, MD, USA
  • fYear
    2014
  • fDate
    27-29 May 2014
  • Firstpage
    539
  • Lastpage
    540
  • Abstract
    We propose a Markov random field (MRF)-based method to segment photographic biomedical images into three image sub-regions, viz., tissue, photo, and background. Segmentation results are then used to extract local and global visual features to separate images with tissue, such as endoscopic images, from general photographs.
  • Keywords
    Markov processes; feature extraction; image retrieval; image segmentation; medical image processing; random processes; MRF model; MRF-based method; Markov random field-based method; background region; biomedical image segmentation; global visual feature extraction; image subregions; local visual feature extraction; photo region; photographic biomedical image segmention; tissue region; Biomedical imaging; Endoscopes; Feature extraction; Image color analysis; Image segmentation; Nickel; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems (CBMS), 2014 IEEE 27th International Symposium on
  • Conference_Location
    New York, NY
  • Type

    conf

  • DOI
    10.1109/CBMS.2014.128
  • Filename
    6881964
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1787363