Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations.

Journal: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Published Date: Mar 1, 2022

Abstract

OBJECTIVES: To develop and validate an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect different patterns of fetal intracranial abnormality in standard sonographic reference planes for screening for congenital central nervous system (CNS) malformations.

Authors

  • M Lin
  • X He
  • H Guo
    Department of Ultrasound, Dongguan Maternal and Child Health Hospital, Dongguan, Guangdong, China.
  • M He
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • L Zhang
    Department of Radiology, Baoji Center Hospital, Baoji, 721008, Shaanxi, China; Department of Radiology, Baoji Hi-Tech People's Hospital, Baoji, 721013, Shaanxi, China.
  • J Xian
    Guangzhou Aiyunji Information Technology Co., Ltd, Guangdong China & School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  • T Lei
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Q Xu
    School of Computer Science, Beijing University of Posts and Telecommunications(National Pilot Software Engineering School), Beijing 100876, China.
  • J Zheng
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
  • J Feng
    Department of Computer Science,University of Warwick,Coventry,UK.
  • C Hao
    Department of Medical Statistics & Sun Yat-sen Global Health Institute, School of Public Health and Institute of State Governance, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Y Yang
    Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China.
  • N Wang
  • H Xie
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.

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