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Application and Progress of Artificial Intelligence in Fetal Ultrasound.
Xiao, Sushan; Zhang, Junmin; Zhu, Ye; Zhang, Zisang; Cao, Haiyan; Xie, Mingxing; Zhang, Li.
Afiliação
  • Xiao S; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Zhang J; Clinical Research Center for Medical Imaging in Hubei Province, Wuhan 430022, China.
  • Zhu Y; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China.
  • Zhang Z; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Cao H; Clinical Research Center for Medical Imaging in Hubei Province, Wuhan 430022, China.
  • Xie M; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China.
  • Zhang L; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
J Clin Med ; 12(9)2023 May 05.
Article em En | MEDLINE | ID: mdl-37176738
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article