Artificial Intelligence in Prenatal Ultrasound Diagnosis

The application of artificial intelligence (AI) technology to medical imaging has resulted in great breakthroughs. Given the unique position of ultrasound (US) in prenatal screening, the research on AI in prenatal US has practical significance with its application to prenatal US diagnosis improving...

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Detalles Bibliográficos
Autores principales: He, Fujiao, Wang, Yaqin, Xiu, Yun, Zhang, Yixin, Chen, Lizhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716504/
https://www.ncbi.nlm.nih.gov/pubmed/34977053
http://dx.doi.org/10.3389/fmed.2021.729978
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author He, Fujiao
Wang, Yaqin
Xiu, Yun
Zhang, Yixin
Chen, Lizhu
author_facet He, Fujiao
Wang, Yaqin
Xiu, Yun
Zhang, Yixin
Chen, Lizhu
author_sort He, Fujiao
collection PubMed
description The application of artificial intelligence (AI) technology to medical imaging has resulted in great breakthroughs. Given the unique position of ultrasound (US) in prenatal screening, the research on AI in prenatal US has practical significance with its application to prenatal US diagnosis improving work efficiency, providing quantitative assessments, standardizing measurements, improving diagnostic accuracy, and automating image quality control. This review provides an overview of recent studies that have applied AI technology to prenatal US diagnosis and explains the challenges encountered in these applications.
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spelling pubmed-87165042021-12-31 Artificial Intelligence in Prenatal Ultrasound Diagnosis He, Fujiao Wang, Yaqin Xiu, Yun Zhang, Yixin Chen, Lizhu Front Med (Lausanne) Medicine The application of artificial intelligence (AI) technology to medical imaging has resulted in great breakthroughs. Given the unique position of ultrasound (US) in prenatal screening, the research on AI in prenatal US has practical significance with its application to prenatal US diagnosis improving work efficiency, providing quantitative assessments, standardizing measurements, improving diagnostic accuracy, and automating image quality control. This review provides an overview of recent studies that have applied AI technology to prenatal US diagnosis and explains the challenges encountered in these applications. Frontiers Media S.A. 2021-12-16 /pmc/articles/PMC8716504/ /pubmed/34977053 http://dx.doi.org/10.3389/fmed.2021.729978 Text en Copyright © 2021 He, Wang, Xiu, Zhang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
He, Fujiao
Wang, Yaqin
Xiu, Yun
Zhang, Yixin
Chen, Lizhu
Artificial Intelligence in Prenatal Ultrasound Diagnosis
title Artificial Intelligence in Prenatal Ultrasound Diagnosis
title_full Artificial Intelligence in Prenatal Ultrasound Diagnosis
title_fullStr Artificial Intelligence in Prenatal Ultrasound Diagnosis
title_full_unstemmed Artificial Intelligence in Prenatal Ultrasound Diagnosis
title_short Artificial Intelligence in Prenatal Ultrasound Diagnosis
title_sort artificial intelligence in prenatal ultrasound diagnosis
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716504/
https://www.ncbi.nlm.nih.gov/pubmed/34977053
http://dx.doi.org/10.3389/fmed.2021.729978
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AT xiuyun artificialintelligenceinprenatalultrasounddiagnosis
AT zhangyixin artificialintelligenceinprenatalultrasounddiagnosis
AT chenlizhu artificialintelligenceinprenatalultrasounddiagnosis

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