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Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation.

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Title: Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation.
Authors: Zhang, Shisheng1, shisheng.zhang@unsw.edu.au, Gharleghi, Ramtin1, Singh, Sonit2, Shen, Chi1, Adikari, Dona3, Zhang, Mingzi1,4, Moses, Daniel5, Vickers, Dominic6, Sowmya, Arcot2, Beier, Susann1
Source: Journal of Imaging Informatics in Medicine; Jun2026, Vol. 39 Issue 3, p2680-2694, 15p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 194225559
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Imaging+Informatics+in+Medicine%22">Journal of Imaging Informatics in Medicine</searchLink>; Jun2026, Vol. 39 Issue 3, p2680-2694, 15p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=194225559
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        Value: 10.1007/s10278-025-01677-2
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 2680
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      – TitleFull: Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation.
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              Text: Jun2026
              Type: published
              Y: 2026
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            – TitleFull: Journal of Imaging Informatics in Medicine
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