• DocumentCode
    3467499
  • Title

    Towards an automatic diagnosis system for skin lesions: Estimation of blue-whitish veil and regression structures

  • Author

    Leo, Giuseppe Di ; Fabbrocini, Gabriella ; Paolillo, Alfredo ; Rescigno, Orsola ; Sommella, Paolo

  • Author_Institution
    DIIIE, Univ. of Salerno, Salerno
  • fYear
    2009
  • fDate
    23-26 March 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper deals with ELM image processing for automatic analysis of pigmented skin lesions which represents one of the greatest challenges of dermatologic practice today. The ldquoELM 7 point checklistrdquo defines a set of seven features, based on colour and texture parameters, which describe the malignancy of a lesion. It has been revealed as faster and with the same accuracy than the traditional ABCD criteria in the diagnosis of melanoma. A preliminary approach to the automated diagnosis of melanocytic skin lesions, based on ELM 7 point checklist is proposed. In particular, the image processing algorithms and classification techniques involved in the automatic detection of the occurrence of two criteria (blue-whitish veil and regression structures) are introduced and the experimental results are reported.
  • Keywords
    feature extraction; image classification; image colour analysis; image texture; medical image processing; regression analysis; skin; ELM 7 point checklist; ELM image processing; automatic diagnosis system; blue-whitish veil; colour-texture parameters; image classification techniques; image processing algorithms; melanocytic skin lesion diagnosis; regression structures; skin lesions; Communication channels; Decoding; Demodulation; Equalizers; Finite impulse response filter; Frequency; Lesions; Skin; Testing; Transfer functions; Biomedical image processing; Dermoscopy; Machine Learning Techniques;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signals and Devices, 2009. SSD '09. 6th International Multi-Conference on
  • Conference_Location
    Djerba
  • Print_ISBN
    978-1-4244-4345-1
  • Electronic_ISBN
    978-1-4244-4346-8
  • Type

    conf

  • DOI
    10.1109/SSD.2009.4956770
  • Filename
    4956770