Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.

Authors

  • Chen Chen
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Yitao Jiang
    Illuminate, LLC, Shenzhen, Guangdong, China; Microport Prophecy, Shanghai, China.
  • Jincao Yao
    Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
  • Min Lai
    Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China; Taizhou Cancer Hospital, Taizhou, China; Key Laboratory of Minimally Invasive Interventional Therapy and Big Data Artificial Intelligence in Medicine of Taizhou, Taizhou, China.
  • Yuanzhen Liu
    Department of Diagnostic Ultrasound Imaging and Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China; Wenling Big Data and Artificial Intelligence Institute in Medicine, Taizhou, Zhejiang 317502, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310018, China. Electronic address: yuanzhen_0128@aliyun.com.
  • Xianping Jiang
    Department of Ultrasound, Shengzhou People's Hospital (the First Affiliated Hospital of Zhejiang University Shengzhou Branch), Shengzhou, 312400, China.
  • Di Ou
    Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
  • Bojian Feng
    Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
  • Lingyan Zhou
    Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China.
  • Jinfeng Xu
    Department of Ultrasound, The Second Clinical Medical College,Jinan University, Guangdong, China.
  • Linghu Wu
    Department of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, 518020, China.
  • Yuli Zhou
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.
  • Wenwen Yue
    Center of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, China. yuewen0902@163.com.
  • Fajin Dong
    Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.
  • Dong Xu
    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.