Deep learning based detection and classification of fetal lip in ultrasound images.

Journal: Journal of perinatal medicine
PMID: 39028804

Abstract

OBJECTIVES: Fetal cleft lip is a common congenital defect. Considering the delicacy and difficulty of observing fetal lips, we have utilized deep learning technology to develop a new model aimed at quickly and accurately assessing the development of fetal lips during prenatal examinations. This model can detect ultrasound images of the fetal lips and classify them, aiming to provide a more objective prediction for the development of fetal lips.

Authors

  • Yapeng Li
    College of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan 430074, China.
  • Peiya Cai
    Department of Gynecology and Obstetrics, Fujian Medical University 2nd Affiliated Hospital, Quanzhou, China.
  • Yubing Huang
    Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
  • Weifeng Yu
    Department of Ultrasound, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China.
  • Zhonghua Liu
    The National and Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha 410081, People's Republic of China. Electronic address: Liuzh@hunnu.edu.cn.
  • Peizhong Liu
    College of Engineering, Huaqiao University, No. 269, Chenghua North Road, Quanzhou, 362021, Fujian, China. pzliu@hqu.edu.cn.

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