Deep learning-based ultrasound diagnostic model for follicular thyroid carcinoma.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: It is challenging to preoperatively diagnose follicular thyroid carcinoma (FTC) on ultrasound images. This study aimed to develop an end-to-end diagnostic model that can classify thyroid tumors into benign tumors, FTC and other malignant tumors based on deep learning.

Authors

  • Yuan Wang
    State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China.
  • Wenliang Lu
    School of Mathematical Sciences, Zhejiang University, Hangzhou, China.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Hao Xu
    Department of Nuclear Medicine, the First Affiliated Hospital, Jinan University, Guangzhou 510632, P.R.China.gdhyx2012@126.com.
  • Dexing Kong
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China. Electronic address: dkong@zju.edu.cn.

Keywords

No keywords available for this article.