Automatic segmentation of dermoscopy images using saliency combined with adaptive thresholding based on wavelet transform

  • Kai HuEmail author
  • Si Liu
  • Yuan Zhang
  • Chunhong Cao
  • Fen Xiao
  • Wei Huang
  • Xieping Gao


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. The proposed method combines the enhanced fusion saliency with adaptive thresholding based on wavelet transform to get the lesion regions. Firstly, a fusion 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. We compare the proposed method with seven state-of-the-art approaches using a series of evaluation metrics on both PH2 and ISBI2016 datasets. The results demonstrate the effectiveness of the proposed method superior to the state-of-the-art approaches in accordance with quantitative results and visual effects.


Saliency map Adaptive thresholding Wavelet transform Dermoscopy images Segmentation 



This work was supported by the National Natural Science Foundation of China under Grants 61802328 and 61771415, and the Cernet Innovation Project under Grant NGII20170702.


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Authors and Affiliations

  1. 1.Key Laboratory of Intelligent Computing and Information Processing of Ministry of EducationXiangtan UniversityXiangtanChina
  2. 2.Postdoctoral Research Station for MechanicsXiangtan UniversityXiangtanChina
  3. 3.Department of RadiologyThe First Hospital of ChangshaChangshaChina

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