A Deep Learning Model for Predicting Molecular Subtype of Breast Cancer by Fusing Multiple Sequences of DCE-MRI From Two Institutes.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: To evaluate the performance of deep learning (DL) in predicting different breast cancer molecular subtypes using DCE-MRI from two institutes.

Authors

  • Xiaoyang Xie
    Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an, 710069, Shaanxi, China.
  • Haowen Zhou
    Department of Statistics, University of Illinois Urbana-Champaign, 725 South Wright Street, Champaign, IL, USA.
  • Mingze Ma
    Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an 710127, Shaanxi, China.
  • Ji Nie
    Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an 710127, Shaanxi, China.
  • Weibo Gao
    Department of Radiology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shannxi, China.
  • Jinman Zhong
    Department of Radiology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shannxi, China.
  • Xin Cao
    Zhongshan Hospital, Institute of Clinical Science, Shanghai Medical College, Fudan University, Shanghai 200032, China.
  • Xiaowei He
  • Jinye Peng
  • Yuqing Hou
    Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an, 710069, Shaanxi, China. houyuqin@nwu.edu.cn.
  • Fengjun Zhao
    Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Science and Technology, Northwest University, Xi'an, 710069, Shaanxi, China. fjzhao@nwu.edu.cn.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.