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A Skin Lesion Segmentation Method Based on Saliency and Adaptive Thresholding in Wavelet Domain

  • Kai HuEmail author
  • Si Liu
  • Yuan Zhang
  • Chunhong Cao
  • Fen Xiao
  • Wei Huang
  • Xieping Gao
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 810)

Abstract

Segmentation is the essential requirement in automated computer-aided diagnosis (CAD) of skin diseases. In this paper, we propose an unsupervised skin lesion segmentation method to challenge the difficulties existing in the dermoscopy images such as low contrast, border indistinct, and skin lesion is close to the boundary. Our method combines the enhanced fusion saliency with adaptive thresholding based on wavelet transform to get the lesion regions. Firstly, the saliency map increases the contract of the skin lesion and healthy skin, and then an adaptive thresholding method based on wavelet transform is used to obtain more accurate lesion regions. Experiments on dermoscopy images demonstrate the effectiveness of the proposed method over several state-of-the-art methods in terms of quantitative results and visual effects.

Keywords

Saliency map Adaptive thresholding Wavelet transform Dermoscopy images Segmentation 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants no. 61802328 and 61771415, and the Cernet Innovation Project under Grant no. NGII20170702.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kai Hu
    • 1
    • 2
    Email author
  • Si Liu
    • 1
  • Yuan Zhang
    • 1
  • Chunhong Cao
    • 1
  • Fen Xiao
    • 1
  • Wei Huang
    • 3
  • Xieping Gao
    • 1
  1. 1.Key Laboratory of Intelligent Computing and Information Processing of Ministry of EducationXiangtan UniversityXiangtanChina
  2. 2.Postdoctoral Research Station for Mechanics, Xiangtan UniversityXiangtanChina
  3. 3.Department of RadiologyThe First Hospital of ChangshaChangshaChina

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