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Open AccessArticle

Surface Mesh Reconstruction from Cardiac MRI Contours

Institute of Biomedical Engineering, University of Oxford, Oxford OX3 7DQ, UK
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This paper is an extended version of our paper published in: Villard B., Carapella V., Ariga R., Grau V., Zacur E. (2017) CardiacMesh Reconstruction from Sparse, Heterogeneous Contours. In: Valdés HernándezM., González-Castro V. (Eds.) Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, Vol. 723. Springer, Cham.
J. Imaging 2018, 4(1), 16; https://doi.org/10.3390/jimaging4010016
Received: 8 November 2017 / Revised: 30 December 2017 / Accepted: 30 December 2017 / Published: 10 January 2018
(This article belongs to the Special Issue Selected Papers from “MIUA 2017”)
We introduce a tool to build a surface mesh able to deal with sparse, heterogeneous, non-parallel, cross-sectional, non-coincidental contours and show its application to reconstruct surfaces of the heart. In recent years, much research has looked at creating personalised 3D anatomical models of the heart. These models usually incorporate a geometrical reconstruction of the anatomy in order to better understand cardiovascular functions as well as predict different cardiac processes. As MRIs are becoming the standard for cardiac medical imaging, we tested our methodology on cardiac MRI data from standard acquisitions. However, the ability to accurately reconstruct heart anatomy in three dimensions commonly comes with fundamental challenges—notably, the trade-off between data fitting and expected visual appearance. Most current techniques can either require contours from parallel slices or, if multiple slice orientations are used, require an exact match between these contours. In addition, some methods introduce a bias by the use of prior shape models or by trade-offs between the data matching terms and the smoothing terms. Our approach uses a composition of smooth approximations towards the maximization of the data fitting, ensuring a good matching to the input data as well as pleasant interpolation characteristics. To assess our method in the task of cardiac mesh generations, we evaluated its performance on synthetic data obtained from a cardiac statistical shape model as well as on real data. Using a statistical shape model, we simulated standard cardiac MRI acquisitions planes and contour data. We performed a multi-parameter evaluation study using plausible cardiac shapes generated from the model. We also show that long axes contours as well as the most extremal slices (basal and apical) contain the most amount of structural information, and thus should be taken into account when generating anatomically relevant geometrical cardiovascular surfaces. Our method is both used on epicardial and endocardial left ventricle surfaces as well as on the right ventricle. View Full-Text
Keywords: heart surface reconstruction; cardiac MRI; contours to mesh reconstruction heart surface reconstruction; cardiac MRI; contours to mesh reconstruction
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MDPI and ACS Style

Villard, B.; Grau, V.; Zacur, E. Surface Mesh Reconstruction from Cardiac MRI Contours. J. Imaging 2018, 4, 16. https://doi.org/10.3390/jimaging4010016

AMA Style

Villard B, Grau V, Zacur E. Surface Mesh Reconstruction from Cardiac MRI Contours. Journal of Imaging. 2018; 4(1):16. https://doi.org/10.3390/jimaging4010016

Chicago/Turabian Style

Villard, Benjamin; Grau, Vicente; Zacur, Ernesto. 2018. "Surface Mesh Reconstruction from Cardiac MRI Contours" J. Imaging 4, no. 1: 16. https://doi.org/10.3390/jimaging4010016

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