• DocumentCode
    3358710
  • Title

    Segmentation of oct skin images by classification of speckle statistical parameters

  • Author

    Ali, Mcheik ; Hadj, Batatia

  • Author_Institution
    Univ. of Toulouse, Toulouse, France
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    613
  • Lastpage
    616
  • Abstract
    This paper deals with segmentation of dermatological OCT images. Classic image segmentation techniques fail to produce accurate results due to the wide presence of speckle. We propose using speckle as source of information in the segmentation process. Different statistical models are analyzed in terms of their ability to differentiate skin layers. The local speckle parameters are used as a features-vector to classify, in a supervised way, different regions. Experimental results are presented using a corpus of twenty three real images delineated by experts. These confirm the potential of the method to generate useful data for robust segmentation.
  • Keywords
    image classification; image segmentation; medical image processing; optical tomography; skin; statistical analysis; vectors; OCT skin image; dermatological OCT images; features-vector; image classification; image segmentation; local speckle parameter; optical coherence tomography; speckle statistical parameter; Adaptive optics; Epidermis; Image segmentation; Nakagami distribution; Pixel; Speckle; OCT; segmentation; speckle modeling; tissue characterization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5653019
  • Filename
    5653019