Deep learning-based differentiation of ventricular septal defect from tetralogy of Fallot in fetal echocardiography images.

Journal: Technology and health care : official journal of the European Society for Engineering and Medicine
PMID: 38759068

Abstract

BACKGROUND: Congenital heart disease (CHD) seriously affects children's health and quality of life, and early detection of CHD can reduce its impact on children's health. Tetralogy of Fallot (TOF) and ventricular septal defect (VSD) are two types of CHD that have similarities in echocardiography. However, TOF has worse diagnosis and higher morality than VSD. Accurate differentiation between VSD and TOF is highly important for administrative property treatment and improving affected factors' diagnoses.

Authors

  • Xia Yu
    Department of Ultrasound, Weihai Maternal and Child Health Hospital, Weihai, China.
  • Liyong Ma
    School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China.
  • Hongjie Wang
    Department of Equipment, Weihai Maternal and Child Health Hospital, Weihai, China.
  • Yong Zhang
    Outpatient Department of Hepatitis, The Sixth Affiliated People's Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Hai Du
    School of Information Science and Engineering, Harbin Institute of Technology, Weihai, Shandong, China.
  • Kaiyuan Xu
    School of Information Science and Engineering, Harbin Institute of Technology, Weihai, Shandong, China.
  • Lianfang Wang
    School of Information Science and Engineering, Harbin Institute of Technology, Weihai, Shandong, China.

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