• DocumentCode
    640983
  • Title

    Fuzzy texture descriptors for early diagnosis of osteoarthritis

  • Author

    Chetty, Girija ; Scarvell, Jennie ; Mitra, Subhasish

  • Author_Institution
    Fac. of ESTeM, Univ. of Canberra, Canberra, ACT, Australia
  • fYear
    2013
  • fDate
    7-10 July 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Knee osteoarthritis (OA) is a debilitating health condition affecting elderly population. Early diagnosis of the disease noninvasively will be very useful, and requires novel image analysis techniques to be developed for processing radiological and MRI scans of knee joints. In this paper, we propose novel micro texture based feature descriptors for modeling subtle variations in MRI T2 maps, so as to facilitate early detection of osteoarthritis. The experimental evaluation of the proposed micro texture descriptors on a publicly available OAI database show, that the proposed features allow a significant improvement in discriminating the textures for MRI T2 maps, corresponding to normal subjects as compared to the subjects with risk factors for developing osteoarthritis.
  • Keywords
    biomedical MRI; diseases; feature extraction; fuzzy set theory; image texture; medical image processing; MRI T2 maps; MRI scan; OAI database; disease diagnosis; elderly population; fuzzy texture descriptor; health condition debilitation; image analysis technique; knee joints; micro texture based feature descriptor; osteoarthritis detection; osteoarthritis diagnosis; radiological processing; Biomarkers; Databases; Feature extraction; Histograms; Magnetic resonance imaging; Osteoarthritis; Fuzzy Logic; Image Analysis; Osteoarthritis; Texture Descriptors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
  • Conference_Location
    Hyderabad
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4799-0020-6
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2013.6622439
  • Filename
    6622439