• DocumentCode
    1907243
  • Title

    Robust Nailfold Capillary Skeleton Extraction

  • Author

    Doshi, Niraj P. ; Schaefer, Gerald ; Merla, Arcangelo

  • Author_Institution
    Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
  • fYear
    2012
  • fDate
    5-7 Nov. 2012
  • Firstpage
    19
  • Lastpage
    23
  • Abstract
    Nail fold capillaroscopy (NC) an inexpensive, non-invasive method to assess capillary morphology, and is routinely used for the detection of scleroderma spectral disorders, Raynaud´s phenomenon and other connective tissue diseases. Evaluation of NC requires expert knowledge and is typically performed by careful manual inspection of the images. Computer-aided approaches of capillary inspection would reduce the time required for diagnosis but have been little pursued due to the challenges present in NC images. In this paper, we present a capillary skeletonisation algorithm based on image enhancement followed by binarisation and skeleton extraction using a thinning algorithm. The extracted vessel skeleton can subsequently be utilised for auto measurement of capillary density and other parameters. We demonstrate that our algorithm works well and that it clearly outperforms previous approaches.
  • Keywords
    automatic optical inspection; biological tissues; diseases; feature extraction; image enhancement; medical disorders; medical image processing; NC images; Raynaud phenomenon; auto measurement; capillary density; capillary inspection; capillary morphology assessment; capillary skeletonisation algorithm; computer-aided approach; diagnosis time reduction; image binarisation; image enhancement; manual image inspection; nailfold capillaroscopy; noninvasive method; robust nailfold capillary skeleton extraction; scleroderma spectral disorder detection; thinning algorithm; tissue diseases; Nailfold capillaroscopy; image analysis; image enhancement; skeletonisation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on
  • Conference_Location
    Himeji
  • ISSN
    2157-0477
  • Print_ISBN
    978-1-4799-0276-7
  • Type

    conf

  • DOI
    10.1109/ICETET.2012.30
  • Filename
    6495201