Comparison of two-dimensional and three-dimensional u-net architectures for segmentation of adipose tissue in cardiac magnetic resonance images

dc.contributor.author	Kulasekara, M.
dc.contributor.author	Dinh, V. Q.
dc.contributor.author	Fernández del Valle, María
dc.contributor.author	Klingensmith, J. D.
dc.date.accessioned	2022-11-08T12:43:18Z
dc.date.available	2022-11-08T12:43:18Z
dc.date.issued	2022
dc.identifier.citation	Medical and Biological Engineering and Computing, 60(8), p. 2291-2306 (2022); doi:10.1007/s11517-022-02612-1
dc.identifier.issn	0140-0118
dc.identifier.uri	http://hdl.handle.net/10651/65430
dc.description.sponsorship	National Heart, Lung, and Blood Institute of the National Institutes of Health [R15HL145576]
dc.format.extent	p. 2291-2306
dc.language.iso	eng
dc.relation.ispartof	Medical and Biological Engineering and Computing
dc.rights	© Springer Nature
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132157667&doi=10.1007%2fs11517-022-02612-1&partnerID=40&md5=01946fa9df41e96671586f5f0d0091dc
dc.title	Comparison of two-dimensional and three-dimensional u-net architectures for segmentation of adipose tissue in cardiac magnetic resonance images
dc.type	journal article
dc.identifier.doi	10.1007/s11517-022-02612-1
dc.relation.publisherversion	http://dx.doi.org/10.1007/s11517-022-02612-1

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