Randomized Dynamic Generation of Selected Melanocytic Skin Lesion Features

  • Zdzisław S. Hippe
  • Jerzy W. Grzymała-Busse
  • Ł. Piątek
Part of the Advances in Soft Computing book series (AINSC, volume 35)


In this paper, the methodology of generating images of melanocytic skin lesions is briefly outlined. The developed methodology proceeds essentially in two steps. In the first one, semantic description of skin lesions of anonymous patients is carefully analyzed to catch important features (symptoms) and to mine their logical values. Then, data gained in this step are used to control a specific simulation process, in which the simulated lesion’s image is randomly put together from a priori pre-defined fragments (textures). In this way, a single textual vector representing a distinct lesion, can produce a collection of several images of a given category. The quality of simulated images, verified by an independent expert was found to be quite satisfactory.


Simulated Image Semantic Description Source Database Melanocytic Lesion Blue Nevus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2006

Authors and Affiliations

  • Zdzisław S. Hippe
    • 1
  • Jerzy W. Grzymała-Busse
    • 1
    • 2
  • Ł. Piątek
    • 3
  1. 1.Department of Expert Systems and Artificial IntelligenceUniversity of Information Technology and ManagementRzeszówPoland
  2. 2.Department of Electrical Engineering and Computer ScienceUniversity of KansasLawrenceUSA
  3. 3.Department of Distributed SystemsUniversity of Information Technology and ManagementRzeszówPoland

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