• DocumentCode
    3086585
  • Title

    Multifractal analysis by the large deviation spectrum to detect osteoporosis

  • Author

    Khider, M. ; Haddad, Bassam ; Ahmed, Abdelmalik Taleb

  • Author_Institution
    Fac. et d´Inf., Univ. des Sci. et de la Technol. Houari Boumedienne, Algiers, Algeria
  • fYear
    2013
  • fDate
    12-15 May 2013
  • Firstpage
    112
  • Lastpage
    115
  • Abstract
    This work is based on the use of the theory of large deviations to calculate the grain multifractal spectrum and classify bone micro architecture texture, to do this the multifractal spectrum mode is used, it gives the fractal dimension of the predominant fractal set to detect osteoporosis. In fact, one of the most relevant parameters to differentiate between pathological and normal cases in the trabecular ROI texture is the distance of separation between trabeculae in bone micro architecture. The method we propose here is based on the multifractal analysis of the signal formed by the succession of bone trabecular thickness and trabecular separation obtained from gray level intensities in the trabecular bone texture to classify the two cases of study.
  • Keywords
    biomedical MRI; fractals; image texture; medical image processing; MRI type; bone micro architecture texture classification; bone trabecular thickness; fractal dimension; grain multifractal spectrum; large deviation spectrum; normal cases; osteoporosis detection; pathological cases; predominant fractal set; trabecular ROI texture; trabecular bone texture; Bones; Correlation; Fractals; Gray-scale; Magnetic resonance imaging; Osteoporosis; Pathology; classification of texture; multifractal spectrum; osteoporosis; theory of large deviations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
  • Conference_Location
    Algiers
  • Type

    conf

  • DOI
    10.1109/WoSSPA.2013.6602346
  • Filename
    6602346