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Alternative Title
Abstract
We propose an automatic algorithm for the reconstruction of patient-specific cardiac mesh models with 1-to-1 vertex correspondence. In this framework, a series of 3D meshes depicting the endocardial surface of the heart at each time step is constructed, based on a set of border delineated magnetic resonance imaging (MRI) data of the whole cardiac cycle. The key contribution in this work involves a novel reconstruction technique to generate a 4D (i.e., spatialtemporal) model of the heart with 1-to-1 vertex mapping throughout the time frames. The reconstructed 3D model from the first time step is used as a base template model and then deformed to fit the segmented contours from the subsequent time steps. A method to determine a tree-based connectivity relationship is proposed to ensure robust mapping during mesh deformation. The novel feature is the ability to handle intra-and inter-frame 2D topology changes of the contours, which manifests as a series of merging and splitting of contours when the images are viewed either in a spatial or temporal sequence. Our algorithm has been tested on five acquisitions of cardiac MRI and can successfully reconstruct the full 4D heart model in around 30 minutes per subject. The generated 4D heart model conforms very well with the input segmented contours and the mesh element shape is of reasonably good quality. The work is important in the support of downstream computational simulation activities. © 2014 Lim et al.
Keywords
1 to 1 vertex correspondence, algorithm, analytical parameters, article, automatic four dimensional reconstruction, cardiac imaging, endocardium, heart cycle, membrane structure, nuclear magnetic resonance imaging, patient specific cardiac mesh model, simulation, three dimensional imaging, tree based connectivity, algorithm, anatomy and histology, audiovisual equipment, automation, biological model, heart, human, nuclear magnetic resonance imaging, three dimensional imaging, time, Algorithms, Automation, Heart, Humans, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Models, Anatomic, Patient-Specific Modeling, Time Factors
Source Title
PLoS ONE
Publisher
Series/Report No.
Collections
Rights
Attribution 4.0 International
Date
2014
DOI
10.1371/journal.pone.0093747
Type
Article