• DocumentCode
    2941657
  • Title

    Characterization of border structure using fractal dimension in melanomas

  • Author

    Carbonetto, S.H. ; Lew, S.E.

  • Author_Institution
    Dept. de Fis., Univ. de Buenos Aires, Buenos Aires, Argentina
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    4088
  • Lastpage
    4091
  • Abstract
    There are many characteristics that differentiate normal moles (nevi) from melanomas. One of them is their boundary irregularity, which can be quantified using Fractal Dimension. In this work, fractal dimension of normal moles and melanoma was computed using the box counting method. These measurements were used to train a linear decoder in order to predict the pathology. The average performance to discriminate normal moles from melanomas reached 85% giving some insights about the power of the fractal dimension as a candidate for automatic detection and diagnosis.
  • Keywords
    edge detection; fractals; medical image processing; patient diagnosis; skin; automatic detection; automatic diagnosis; border structure characterization; boundary irregularity; box counting method; fractal dimension; linear decoder training; melanomas; normal moles; pathology prediction; Cancer; Estimation; Fractals; Malignant tumors; Skin; Testing; Training; Fractals; Humans; Melanoma; Skin Neoplasms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5627296
  • Filename
    5627296