• DocumentCode
    1770677
  • Title

    Automatic detection of skin melanoma from images using natural computing approaches

  • Author

    Dumitrache, Ioana ; Sultana, Alina Elena ; Dogaru, Radu

  • Author_Institution
    Doctoral Sch. on Electron., Telecommun. & Inf. Technol., Univ. “Politeh.” Bucharest, Bucharest, Romania
  • fYear
    2014
  • fDate
    29-31 May 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Medical imaging is an area of great interest in terms of accuracy, speed and capacity of integration. In order to improve results and ease the physicians´ task, some feature enhancement and image processing should be done automatically in order to lead to some features that allow an automatic classification of the images. This paper presents an original approach to construct an automatic melanoma detection system, based on employing natural computing methods for image preprocessing, feature extraction and classification. Among these methods we rely on cellular automata, reaction diffusion cellular neural networks, nonlinear time-series analysis.
  • Keywords
    cancer; cellular automata; cellular neural nets; feature extraction; image classification; medical image processing; reaction-diffusion systems; skin; time series; automatic skin melanoma detection system; cellular automata; feature extraction; image classification; image preprocessing; medical imaging; natural computing approach; nonlinear time series analysis; reaction diffusion cellular neural network; Cellular neural networks; Databases; Image segmentation; Lesions; Malignant tumors; Skin; Support vector machines; Image processing; Support Vector Machine; automatic classification; cellular automata; feature extraction; medical imaging; nonlinear dynamics; reaction-diffusion cellular neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (COMM), 2014 10th International Conference on
  • Conference_Location
    Bucharest
  • Type

    conf

  • DOI
    10.1109/ICComm.2014.6866748
  • Filename
    6866748