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Automated Detection of Melanoma in Dermoscopic Images

  • Jose Luis García Arroyo
  • Begoña García Zapirain
Chapter
Part of the Series in BioEngineering book series (SERBIOENG)

Abstract

In this chapter a software system for the automated detection of melanoma over dermoscopic images is presented. The analysis is carried out by supporting in the “ABCD Rule” medical algorithm, undertaking the automated detection and characterization of the corresponding indicators. For this purpose the system uses different image processing techniques and three supervised machine learning tasks. To test the robustness of the system the different indicators of the algorithm are tested, obtaining good results of accuracy in all of them, and there also was determined in a direct way the diagnostic capacity of the system, obtaining results of 81.25 % of sensitivity and 77.14 % of specificity. Moreover, the system is also capable of analyzing macroscopic images, having been designd with multiplatform architecture and being firmly oriented to teledermatology, which is increasingly used.

Keywords

Melanoma Segmentation Biosignal processing techniques Pattern recognition Machine learning 

Notes

Acknowledgments

The authors wish to acknowledge the help of the companies GAIA, IMQ and Maser, as well as the support provided by the Basque Country Government Departments of Education and Industry, Commerce and Tourism.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jose Luis García Arroyo
    • 1
  • Begoña García Zapirain
    • 1
  1. 1.DeustoTech-LIFE Laboratory, Faculty of EngineeringUniversity of DeustoBilbaoSpain

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