Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0145570
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dc.titleVariational reconstruction of left cardiac structure from CMR images
dc.contributor.authorWan M.
dc.contributor.authorHuang W.
dc.contributor.authorZhang J.-M.
dc.contributor.authorZhao X.
dc.contributor.authorTan R.S.
dc.contributor.authorWan X.
dc.contributor.authorZhong L.
dc.date.accessioned2019-11-06T08:06:26Z
dc.date.available2019-11-06T08:06:26Z
dc.date.issued2015
dc.identifier.citationWan M., Huang W., Zhang J.-M., Zhao X., Tan R.S., Wan X., Zhong L. (2015). Variational reconstruction of left cardiac structure from CMR images. PLoS ONE 10 (12) : e0145570. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0145570
dc.identifier.issn19326203
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161598
dc.description.abstractCardiovascular Disease (CVD), accounting for 17% of overall deaths in the USA, is the leading cause of death over the world. Advances in medical imaging techniques make the quantitative assessment of both the anatomy and function of heart possible. The cardiac modeling is an invariable prerequisite for quantitative analysis. In this study, a novel method is proposed to reconstruct the left cardiac structure from multi-planed cardiac magnetic resonance (CMR) images and contours. Routine CMR examination was performed to acquire both long axis and short axis images. Trained technologists delineated the endocardial contours. Multiple sets of two dimensional contours were projected into the three dimensional patientbased coordinate system and registered to each other. The union of the registered point sets was applied a variational surface reconstruction algorithm based on Delaunay triangulation and graph-cuts. The resulting triangulated surfaces were further post-processed. Quantitative evaluation on our method was performed via computing the overlapping ratio between the reconstructed model and the manually delineated long axis contours, which validates our method. We envisage that this method could be used by radiographers and cardiologists to diagnose and assess cardiac function in patients with diverse heart diseases. � 2015 Wan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjectalgorithm
dc.subjectArticle
dc.subjectcardiovascular magnetic resonance
dc.subjectcontrolled study
dc.subjecthuman
dc.subjecthuman experiment
dc.subjectimage reconstruction
dc.subjectleft cardiac structure
dc.subjectmathematical computing
dc.subjectmeasurement accuracy
dc.subjectmorphology
dc.subjectnormal human
dc.subjectquantitative analysis
dc.subjectsurface property
dc.subjectvalidation process
dc.subjectanatomy and histology
dc.subjectbiological model
dc.subjectcine magnetic resonance imaging
dc.subjectcomputer assisted diagnosis
dc.subjectheart
dc.subjectphysiology
dc.subjectprocedures
dc.subjectAlgorithms
dc.subjectHeart
dc.subjectHumans
dc.subjectImage Interpretation, Computer-Assisted
dc.subjectMagnetic Resonance Imaging, Cine
dc.subjectModels, Cardiovascular
dc.typeArticle
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.contributor.departmentDEAN'S OFFICE (DUKE-NUS MEDICAL SCHOOL)
dc.description.doi10.1371/journal.pone.0145570
dc.description.sourcetitlePLoS ONE
dc.description.volume10
dc.description.issue12
dc.description.pagee0145570
dc.published.statePublished
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This item is licensed under a Creative Commons License Creative Commons