Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0145570
Title: Variational reconstruction of left cardiac structure from CMR images
Authors: Wan M.
Huang W.
Zhang J.-M. 
Zhao X.
Tan R.S. 
Wan X.
Zhong L. 
Keywords: algorithm
Article
cardiovascular magnetic resonance
controlled study
human
human experiment
image reconstruction
left cardiac structure
mathematical computing
measurement accuracy
morphology
normal human
quantitative analysis
surface property
validation process
anatomy and histology
biological model
cine magnetic resonance imaging
computer assisted diagnosis
heart
physiology
procedures
Algorithms
Heart
Humans
Image Interpretation, Computer-Assisted
Magnetic Resonance Imaging, Cine
Models, Cardiovascular
Issue Date: 2015
Citation: Wan 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
Abstract: Cardiovascular 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.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161598
ISSN: 19326203
DOI: 10.1371/journal.pone.0145570
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