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Dermoscopy Image Processing for Chinese

Chapter
Part of the Series in BioEngineering book series (SERBIOENG)

Abstract

Dermoscopy image analysis technology is discussed based on Chinese in this chapter. It includes four aspects: preprocessing, segmentation, feature extraction and classification. Firstly, in preprocessing stage, hair is extracted out according to the elongate of connected region, and then removed from the image by using PDE-based image inpainting technology. Secondly, a novel dermoscopy image segmentation algorithm is introduced using self-generating neural network (SGNN) combined with genetic algorithm (GA). And in the feature description stage, the features including color, texture, shape and border are extracted for the lesion object. Lastly, the model of combined neural network classifier is employed to classify the lesion object successfully with a sensitivity and specificity of 93.3 and 96.7 % respectively. Based on the image analysis method disscussed in this chapter, an automatic analysis system of dermoscopy images of Chinese is successfully developed and has been applied for the clinical diagnosis of skin tumors.

Keywords

hair removal PDE-based inpainting automatic segmentation  self-generating neural network feature extraction lesion object classification combined neural network classifier 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Fengying Xie
    • 1
  • Yefen Wu
    • 1
  • Zhiguo Jiang
    • 1
  • Rusong Meng
    • 2
  1. 1.School of astronauticsBeihang UniversityBeijingChina
  2. 2.Department of DermatologyGeneral Hospital of the Air Force of the Chinese People’s Liberation ArmyBeijingChina

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