Automatic 4D Reconstruction of Patient-Specific Cardiac Mesh with 1-to-1 Vertex Correspondence from Segmented Contours Lines

• Published in: PloS one Vol. 9; no. 4; p. e93747
• Main Authors: Lim, Chi Wan, Su, Yi, Yeo, Si Yong, Ng, Gillian Maria, Nguyen, Vinh Tan, Zhong, Liang, Tan, Ru San, Poh, Kian Keong, Chai, Ping
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.04.2014; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Automation; Biology and Life Sciences; Cardiovascular diseases; Care and treatment; Computer and Information Sciences; Computer applications; Computer simulation; Contours; Deformation; Diagnosis; Disease; Engineering and Technology; Finite element method; Fluid dynamics; Heart; Heart - anatomy & histology; Heart diseases; Humans; Imaging, Three-Dimensional; Magnetic resonance; Magnetic Resonance Imaging; Mapping; Medical imaging; Medicine and Health Sciences; Models, Anatomic; NMR; Nuclear magnetic resonance; Patient-Specific Modeling; Physical Sciences; Reconstruction; Risk factors; Splitting; Three dimensional models; Time Factors; Topology; Singapore
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0093747

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., spatial-temporal) 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.