Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding

Gudigar, A; Raghavendra, U; Samanth, J; Vasudeva, A; Ashwal, AJ; Nayak, K; Tan, RS; Ciaccio, EJ; Ooi, CP; Barua, PD; Molinari, F; Acharya, UR

Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding

Gudigar, A Raghavendra, U Samanth, J Vasudeva, A Ashwal, AJ Nayak, K Tan, RS Ciaccio, EJ Ooi, CP Barua, PD Molinari, F Acharya, UR

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Informatics, 2022, 9, (2), pp. 34
Issue Date:: 2022-06-01

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Field	Value	Language
dc.contributor.author	Gudigar, A
dc.contributor.author	Raghavendra, U
dc.contributor.author	Samanth, J
dc.contributor.author	Vasudeva, A
dc.contributor.author	Ashwal, AJ
dc.contributor.author	Nayak, K
dc.contributor.author	Tan, RS
dc.contributor.author	Ciaccio, EJ
dc.contributor.author	Ooi, CP
dc.contributor.author	Barua, PD
dc.contributor.author	Molinari, F
dc.contributor.author	Acharya, UR
dc.date.accessioned	2023-03-27T03:56:25Z
dc.date.available	2023-03-27T03:56:25Z
dc.date.issued	2022-06-01
dc.identifier.citation	Informatics, 2022, 9, (2), pp. 34
dc.identifier.issn	2227-9709
dc.identifier.issn	2227-9709
dc.identifier.uri	http://hdl.handle.net/10453/168575
dc.description.abstract	The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child’s outcomes. In this regard, artificial intelligence (AI) can be used for the automatic analysis of fetal heart ultrasound images. This study reviews nondeep and deep learning approaches for assessing the fetal heart using standard four-chamber ultrasound images. The state-of-the-art techniques in the field are described and discussed. The compendium demonstrates the capability of automatic assessment of the fetal heart using AI technology. This work can serve as a resource for research in the field.
dc.language	en
dc.publisher	MDPI
dc.relation.ispartof	Informatics
dc.relation.isbasedon	10.3390/informatics9020034
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0806 Information Systems, 0807 Library and Information Studies
dc.title	Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding
dc.type	Journal Article
utslib.citation.volume	9
utslib.for	0806 Information Systems
utslib.for	0807 Library and Information Studies
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2023-03-27T03:56:24Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	9
utslib.citation.issue	2

Abstract:

The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child’s outcomes. In this regard, artificial intelligence (AI) can be used for the automatic analysis of fetal heart ultrasound images. This study reviews nondeep and deep learning approaches for assessing the fetal heart using standard four-chamber ultrasound images. The state-of-the-art techniques in the field are described and discussed. The compendium demonstrates the capability of automatic assessment of the fetal heart using AI technology. This work can serve as a resource for research in the field.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/168575