Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.

Journal: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Published Date: Oct 1, 2020

Abstract

OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.

Authors

  • H N Xie
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • N Wang
  • M He
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • L H Zhang
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • H M Cai
    School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  • J B Xian
    Guangzhou Aiyunji Information Technology Co., Ltd, Guangdong, China.
  • M F Lin
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • J Zheng
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Y Z Yang
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.

Keywords

External Resources

Popular Topics
Recent Journals