Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To evaluate the prediction performance of deep convolutional neural network (DCNN) based on ultrasound (US) images for the assessment of breast cancer molecular subtypes.

Authors

  • Meng Jiang
    Affiliated Hospital of Nanjing University of TCM, Jiangsu Provincial Hospital of TCM, Nanjing 210029,China.
  • Di Zhang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Shi-Chu Tang
    Department of Medical Ultrasound, Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, Hunan, China.
  • Xiao-Mao Luo
    Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
  • Zhi-Rui Chuan
    Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
  • Wen-Zhi Lv
    Department of Artificial Intelligence, Julei Technology Company, Wuhan, 430030, China.
  • Fan Jiang
    Department of Medical Ultrasound, The Second Hospital of Anhui Medical University, Hefei, China.
  • Xue-Jun Ni
    Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China.
  • Xin-Wu Cui
    Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Christoph F Dietrich
    Sino-German Tongji-Caritas Research Center of Ultrasound in Medicine, Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.