Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0068615
Title: A Geometrical Approach for Automatic Shape Restoration of the Left Ventricle
Authors: Tan M.-L.
Su Y.
Lim C.-W.
Selvaraj S.K.
Zhong L. 
Tan R.-S. 
Keywords: accuracy
algorithm
article
artifact
automatic algorithm
automatic shape restoration
clinical article
controlled study
geometry
heart function
heart left ventricle size
human
image analysis
image display
image reconstruction
in vivo study
mathematical analysis
nuclear magnetic resonance imaging
process optimization
simulation
Algorithms
Artifacts
Computer Simulation
Heart Ventricles
Humans
Imaging, Three-Dimensional
Magnetic Resonance Imaging
Ventricular Remodeling
Issue Date: 2013
Citation: Tan M.-L., Su Y., Lim C.-W., Selvaraj S.K., Zhong L., Tan R.-S. (2013). A Geometrical Approach for Automatic Shape Restoration of the Left Ventricle. PLoS ONE 8 (7) : e68615. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0068615
Abstract: This paper describes an automatic algorithm that uses a geometry-driven optimization approach to restore the shape of three-dimensional (3D) left ventricular (LV) models created from magnetic resonance imaging (MRI) data. The basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration and that the general shape characteristic of the LV is not altered. The Maximum Principle Curvature (k1) and the Minimum Principle Curvature (k2) of the LV epicardial surface are used to construct a shape-based optimization objective function to restore the shape of a motion-affected LV via a dual-resolution semi-rigid deformation process and a free-form geometric deformation process. A limited memory quasi-Newton algorithm, L-BFGS-B, is then used to solve the optimization problem. The goal of the optimization is to achieve a smooth epicardial shape by iterative in-plane and through-plane translation of vertices in the LV model. We tested our algorithm on 30 sets of LV models with simulated motion artifact generated from a very smooth patient sample, and 20 in vivo patient-specific models which contain significant motion artifacts. In the 30 simulated samples, the Hausdorff distances with respect to the Ground Truth are significantly reduced after restoration, signifying that the algorithm can restore geometrical accuracy of motion-affected LV models. In the 20 in vivo patient-specific models, the results show that our method is able to restore the shape of LV models without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings. © 2013 Tan et al.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161288
ISSN: 19326203
DOI: 10.1371/journal.pone.0068615
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