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An image segmentation method based on network clustering model

Author

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  • Jiao, Yang
  • Wu, Jianshe
  • Jiao, Licheng

Abstract

Network clustering phenomena are ubiquitous in nature and human society. In this paper, a method involving a network clustering model is proposed for mass segmentation in mammograms. First, the watershed transform is used to divide an image into regions, and features of the image are computed. Then a graph is constructed from the obtained regions and features. The network clustering model is applied to realize clustering of nodes in the graph. Compared with two classic methods, the algorithm based on the network clustering model performs more effectively in experiments.

Suggested Citation

  • Jiao, Yang & Wu, Jianshe & Jiao, Licheng, 2018. "An image segmentation method based on network clustering model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1532-1542.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:1532-1542
    DOI: 10.1016/j.physa.2017.08.118
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    References listed on IDEAS

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    1. Chen, Huan & Mai, Yong & Li, Sai-Ping, 2014. "Analysis of network clustering behavior of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 360-367.
    2. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
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