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Advances in the Application of Artificial Intelligence in Fetal Echocardiography.
Zhang, Junmin; Xiao, Sushan; Zhu, Ye; Zhang, Zisang; Cao, Haiyan; Xie, Mingxing; Zhang, Li.
Affiliation
  • Zhang J; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Xiao S; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Zhu Y; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Zhang Z; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Cao H; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Xie M; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
  • Zhang L; Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinical Research Center for Medical Imaging, Hubei Province, Wuhan, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China. Electronic address: zl
J Am Soc Echocardiogr ; 37(5): 550-561, 2024 May.
Article in En | MEDLINE | ID: mdl-38199332
ABSTRACT
Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning can significantly improve fetal survival rates. Echocardiography is one of the most accessible and widely used diagnostic tools in the diagnosis of fetal congenital heart disease. However, traditional fetal echocardiography has limitations due to fetal, maternal, and ultrasound equipment factors and is highly dependent on the skill level of the operator. Artificial intelligence (AI) technology, with its rapid development utilizing advanced computer algorithms, has great potential to empower sonographers in time-saving and accurate diagnosis and to bridge the skill gap in different regions. In recent years, AI-assisted fetal echocardiography has been successfully applied to a wide range of ultrasound diagnoses. This review systematically reviews the applications of AI in the field of fetal echocardiography over the years in terms of image processing, biometrics, and disease diagnosis and provides an outlook for future research.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Echocardiography / Ultrasonography, Prenatal / Fetal Heart / Heart Defects, Congenital Type of study: Screening_studies Limits: Female / Humans / Pregnancy Language: En Journal: J Am Soc Echocardiogr Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Echocardiography / Ultrasonography, Prenatal / Fetal Heart / Heart Defects, Congenital Type of study: Screening_studies Limits: Female / Humans / Pregnancy Language: En Journal: J Am Soc Echocardiogr Journal subject: DIAGNOSTICO POR IMAGEM Year: 2024 Document type: Article Affiliation country: China