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Intelligent Segmentation and Classification of Pigmented Skin Lesions in Dermatological Images

  • Ilias Maglogiannis
  • Elias Zafiropoulos
  • Christos Kyranoudis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3955)

Abstract

During the last years, computer vision-based diagnostic systems have been used in several hospitals and dermatology clinics, aiming mostly at the early detection of malignant melanoma tumor, which is among the most frequent types of skin cancer, versus other types of non-malignant cutaneous diseases. In this paper we discuss intelligent techniques for the segmentation and classification of pigmented skin lesions in such dermatological images. A local thresholding algorithm is proposed for skin lesion separation and border, texture and color based features, are then extracted from the digital images. Extracted features are used to construct a classification module based on Support Vector Machines (SVM) for the recognition of malignant melanoma versus dysplastic nevus.

Keywords

Support Vector Machine Skin Lesion Dysplastic Nevus Pigment Skin Lesion True Color Image 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ilias Maglogiannis
    • 1
  • Elias Zafiropoulos
    • 1
  • Christos Kyranoudis
    • 2
  1. 1.Department of Information and Communication Systems EngineeringUniversity of the AegeanKarlovasi, SamosGreece
  2. 2.School of Chemical EngineeringNational Technical University of AthensAthensGreece

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