Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Active shape models—their training and application
Computer Vision and Image Understanding
An Adaptive-Focus Deformable Model Using Statistical and Geometric Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia
LV surface reconstruction from sparse TMRI using Laplacian surface deformation and optimization
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Reconstruction of detailed left ventricle motion from TMRI using deformable models
FIMH'07 Proceedings of the 4th international conference on Functional imaging and modeling of the heart
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In this paper, we present an effective algorithmto construct a 3D shape atlas for the left ventricle of heart from cardiac Magnetic Resonance Image data. We derive a framework that creates a 3D object mesh from a 2D stack of contours, based on geometry processing algorithms and a semi-constrained deformation method. The geometry processing methods include decimation, detail preserved smoothing and isotropic remeshing, and they ensure high-quality meshes. The deformation method generates subject-specific 3D models, but with global point correspondences. Once we extract 3D meshes from the sample data, generalized Procrustes analysis and Principal Component Analysis are then applied to align them together and model the shape variations. We demonstrate the algorithm via a set of experiments on a population of cardiac MRI scans. We also present modes of variation from the computed atlas for the control population, to show the shape and motion variability.