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Application and Progress of Artificial Intelligence in Fetal Ultrasound
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 arti...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179567/ https://www.ncbi.nlm.nih.gov/pubmed/37176738 http://dx.doi.org/10.3390/jcm12093298 |
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author | Xiao, Sushan Zhang, Junmin Zhu, Ye Zhang, Zisang Cao, Haiyan Xie, Mingxing Zhang, Li |
author_facet | Xiao, Sushan Zhang, Junmin Zhu, Ye Zhang, Zisang Cao, Haiyan Xie, Mingxing Zhang, Li |
author_sort | Xiao, Sushan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10179567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101795672023-05-13 Application and Progress of Artificial Intelligence in Fetal Ultrasound Xiao, Sushan Zhang, Junmin Zhu, Ye Zhang, Zisang Cao, Haiyan Xie, Mingxing Zhang, Li J Clin Med Review 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. MDPI 2023-05-05 /pmc/articles/PMC10179567/ /pubmed/37176738 http://dx.doi.org/10.3390/jcm12093298 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Xiao, Sushan Zhang, Junmin Zhu, Ye Zhang, Zisang Cao, Haiyan Xie, Mingxing Zhang, Li Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title | Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title_full | Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title_fullStr | Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title_full_unstemmed | Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title_short | Application and Progress of Artificial Intelligence in Fetal Ultrasound |
title_sort | application and progress of artificial intelligence in fetal ultrasound |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179567/ https://www.ncbi.nlm.nih.gov/pubmed/37176738 http://dx.doi.org/10.3390/jcm12093298 |
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