Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.

Journal: Medical physics
Published Date: Nov 28, 2018

Abstract

PURPOSE: Due to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it can effectively extract representative features from lesions and the background in BUS images.

Authors

  • Yuzhou Hu
    Departmentof Electronic Engineering, Fudan University, Shanghai, 200433, China.
  • Yi Guo
    Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Yuanyuan Wang
    Department of Biotechnology, College of Life Science and Technology, Jinan University Guangzhou, 510632, China.
  • Jinhua Yu
    Department of Electronic Engineering, Fudan University, Shanghai, 200433, China. jhyu@fudan.edu.cn.
  • Jiawei Li
    School of Chemistry & Chemical Engineering, College of Guangling, Yangzhou University Yangzhou 225002 PR China zhuxiashi@sina.com.
  • Shichong Zhou
    Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
  • Cai Chang
    Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.

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