Skin lesion segmentation using high-resolution convolutional neural network.

Journal: Computer methods and programs in biomedicine
Published Date: Dec 4, 2019

Abstract

BACKGROUND AND OBJECTIVE: Skin lesion segmentation is an important but challenging task in computer-aided diagnosis of dermoscopy images. Many segmentation methods based on convolutional neural networks often fail to extract accurate lesion boundaries because the spatial size of feature maps decreases as the maps are processed throughout the network layers. We propose skin lesion segmentation in dermoscopy images based on a convolutional neural network with an attention mechanism, which can preserve edge details.

Authors

  • Fengying Xie
  • Jiawen Yang
    Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100191, China.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Zhiguo Jiang
  • Yushan Zheng
    Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100191, China.
  • Yukun Wang
    Institute of Sport Business, Loughborough University London, London, United Kingdom.

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