Comparative study of 2D vs. 3D AI-enhanced ultrasound for fetal crown-rump length evaluation in the first trimester.

Journal: BMC pregnancy and childbirth
Published Date: Jul 16, 2025

Abstract

BACKGROUND: Accurate fetal growth evaluation is crucial for monitoring fetal health, with crown-rump length (CRL) being the gold standard for estimating gestational age and assessing growth during the first trimester. To enhance CRL evaluation accuracy and efficiency, we developed an artificial intelligence (AI)-based model (3DCRL-Net) using the 3D U-Net architecture for automatic landmark detection to achieve CRL plane localization and measurement in 3D ultrasound. We then compared its performance to that of experienced radiologists using both 2D and 3D ultrasound for fetal growth assessment.

Authors

  • Yuanji Zhang
    Department of Ultrasound, Luohu People's Hospital, Shenzhen, China.
  • Yuhao Huang
    Department of Neurosurgery, Stanford University School of Medicine, Palo Alto, CA, USA. yhhuang@stanford.edu.
  • Chaoyu Chen
    National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China; Medical Ultrasound Image Computing (MUSIC) Laboratory, Shenzhen University, Shenzhen, China.
  • Xing Hu
    State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China.
  • Wenxiong Pan
    School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, China.
  • Huanjia Luo
    Department of Ultrasound, Huizhou Central People's Hospital, Huizhou, Guangdong, China.
  • Yankai Huang
    Department of Ultrasound, Southern Medical University Shenzhen Hospital, Shenzhen, China.
  • Haixia Wang
    Department of Ultrasound, Luohu People's Hospital, Shenzhen, China.
  • Yan Cao
    School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai, 200433, China.
  • Yan Yi
    Departments of Radiology, Peking Union Medical College Hospital, Beijing.
  • Yi Xiong
    Departement of Medical Oncology, Lung Cancer and Gastrointestinal Unit, Hunan Cancer Hospital/Affiliated Cancer Hospital of Xiangya School of Medicine, Changsha 410013, China.
  • Dong Ni

Keywords

External Resources

Popular Topics
Recent Journals