Application and Progress of Artificial Intelligence in Fetal Ultrasound

被引:15
作者
Xiao, Sushan [1 ,2 ,3 ]
Zhang, Junmin [1 ,2 ,3 ]
Zhu, Ye [1 ,2 ,3 ]
Zhang, Zisang [1 ,2 ,3 ]
Cao, Haiyan [1 ,2 ,3 ]
Xie, Mingxing [1 ,2 ,3 ]
Zhang, Li [1 ,2 ,3 ]
机构
[1] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Ultrasound Med, Wuhan 430022, Peoples R China
[2] Clin Res Ctr Med Imaging Hubei Prov, Wuhan 430022, Peoples R China
[3] Hubei Prov Key Lab Mol Imaging, Wuhan 430022, Peoples R China
基金
中国国家自然科学基金;
关键词
fetal ultrasound; artificial intelligence; prenatal diagnosis; deep learning; convolution neural network; NAVIGATION ECHOCARDIOGRAPHY FINE; CENTRAL-NERVOUS-SYSTEM; GESTATIONAL-AGE; SONOGRAPHIC EXAMINATION; GUIDELINES; IMAGES;
D O I
10.3390/jcm12093298
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However, problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter-observer variability limit the development of traditional ultrasound in clinical applications. The combination of artificial intelligence (AI) and obstetric ultrasound may help optimize fetal ultrasound examination by shortening the examination time, reducing the physician's workload, and improving diagnostic accuracy. AI has been successfully applied to automatic fetal ultrasound standard plane detection, biometric parameter measurement, and disease diagnosis to facilitate conventional imaging approaches. In this review, we attempt to thoroughly review the applications and advantages of AI in prenatal fetal ultrasound and discuss the challenges and promises of this new field.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Editorial: Ultrasound in Oncology: Application of Big Data and Artificial Intelligence
    Shen, Yu-Ting
    Yue, Wen-Wen
    Xu, Hui-Xiong
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [42] Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination
    Stirnemann, J. J.
    Besson, R.
    Spaggiari, E.
    Rojo, S.
    Loge, F.
    Peyro-Saint-Paul, H.
    Allassonniere, S.
    Le Pennec, E.
    Hutchinson, C.
    Sebire, N.
    Ville, Y.
    ULTRASOUND IN OBSTETRICS & GYNECOLOGY, 2023, 62 (03) : 353 - 360
  • [43] Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence
    Hiroko Satake
    Satoko Ishigaki
    Rintaro Ito
    Shinji Naganawa
    La radiologia medica, 2022, 127 : 39 - 56
  • [44] Application of artificial intelligence in ophthalmology
    Xue-Li Du
    Wen-Bo Li
    Bo-Jie Hu
    International Journal of Ophthalmology, 2018, (09) : 1555 - 1561
  • [45] The application of artificial intelligence in EUS
    Zhang, Deyu
    Wu, Chang
    Yang, Zhenghui
    Yin, Hua
    Liu, Yue
    Li, Wanshun
    Huang, Haojie
    Jin, Zhendong
    ENDOSCOPIC ULTRASOUND, 2024, 13 (02) : 65 - 75
  • [46] Application of artificial intelligence in gastroenterology
    Yang, Young Joo
    Bang, Chang Seok
    WORLD JOURNAL OF GASTROENTEROLOGY, 2019, 25 (14) : 1666 - 1683
  • [47] Application of artificial intelligence in gastroenterology
    Young Joo Yang
    Chang Seok Bang
    World Journal of Gastroenterology, 2019, (14) : 1666 - 1683
  • [48] Application of artificial intelligence in surgery
    Xiao-Yun Zhou
    Yao Guo
    Mali Shen
    Guang-Zhong Yang
    Frontiers of Medicine, 2020, 14 : 417 - 430
  • [49] Progress of Artificial Intelligence in Gynecological Malignant Tumors
    Zhou, Jie
    Zeng, Zhi Ying
    Li, Li
    CANCER MANAGEMENT AND RESEARCH, 2020, 12 : 12823 - 12840
  • [50] Application of artificial intelligence in ophthalmology
    Du, Xue-Li
    Li, Wen-Bo
    Hu, Bo-Jie
    INTERNATIONAL JOURNAL OF OPHTHALMOLOGY, 2018, 11 (09) : 1555 - 1561