Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date:

Abstract

BACKGROUND: Accurate diagnosis of breast lesions and discrimination of axillary lymph node (ALN) metastases largely depend on radiologist experience.

Authors

  • Heng Zhou
    School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai, Shandong, China.
  • Zhen Hua
    School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai, Shandong, China.
  • Jing Gao
    Department of Gastroenterology 3, Hubei University of Medicine, Renmin Hospital, Shiyan, Hubei, China.
  • Fan Lin
    Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yuqian Chen
  • Shijie Zhang
    Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China. shijie.zhang@tmu.edu.cn.
  • Tiantian Zheng
    Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, 264000, Yantai, Shandong, P. R. China.
  • Zhongyi Wang
    Information Office, Henan University of Chinese Medicine, Zhengzhou 450046, China.
  • Huafei Shao
    Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, People's Republic of China.
  • Wenjuan Li
    Faculty of Chemistry and Material Science, Langfang Normal University, Langfang 065000, Hebei, China.
  • Fengjie Liu
    Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, China.
  • Qin Li
    Department of Spine Surgery, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
  • Jingjing Chen
    Department of Cardiovascular Medicine, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Ximing Wang
  • Feng Zhao
    Department of Blood Transfusion, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Nina Qu
    Department of Ultrasound, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, China.
  • Haizhu Xie
    Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, People's Republic of China.
  • Heng Ma
    Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, People's Republic of China.
  • Haicheng Zhang
    Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, People's Republic of China.
  • Ning Mao
    Department of Radiology, Peking University People's Hospital, 11 Xizhimen Nandajie, Xicheng District, Beijing, 100044, People's Republic of China.