Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia
Metamorphs: Deformable Shape and Appearance Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Robust mesh editing using Laplacian coordinates
Graphical Models
Construction of left ventricle 3D shape atlas from cardiac MRI
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
4D cardiac reconstruction using high resolution CT images
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
Progressive surface reconstruction for heart mapping procedure
Computer-Aided Design
3D anatomical shape atlas construction using mesh quality preserved deformable models
Computer Vision and Image Understanding
Pattern Recognition and Image Analysis
Sparse deformable models with application to cardiac motion analysis
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
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We propose a novel framework to reconstruct the left ventricle (LV)'s 3D surface from sparse tagged-MRI (tMRI). First we acquire an initial surface mesh from a dense tMRI. Then landmarks are calculated both on contours of a specific new tMRI data and on corresponding slices of the initial mesh. Next, we employ several filters including global deformation, local deformation and remeshing to deform the initial surface mesh to the image data. This step integrates Polar Decomposition, Laplacian Surface Optimization (LSO) and Deformation (LSD) algorithms. The resulting mesh represents the reconstructed surface of the image data. Further more, this high quality surface mesh can be adopted by most deformable models. Using tagging line information, these models can reconstruct LV motion. The experimental results show that compared to Thin Plate Spline (TPS) our algorithm is relatively fast, the shape represents image data better and the triangle quality is more suitable for deformable model.