Adaptive-Focus Statistical Shape Model for Segmentation of 3D MR Structures
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
LV Motion and Strain Computation from tMRI Based on Meshless Deformable Models
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
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
Multi-surface cardiac modelling, segmentation, and tracking
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
3D anatomical shape atlas construction using mesh quality preserved deformable models
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
3D anatomical shape atlas construction using mesh quality preserved deformable models
Computer Vision and Image Understanding
A survey of shaped-based registration and segmentation techniques for cardiac images
Computer Vision and Image Understanding
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
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Recent developments on the 320 multi-detector CT technologies have made the volumetric acquisition of 4D high resolution cardiac images in a single heart beat possible. In this paper, we present a framework that uses these data to reconstruct the 4D motion of the endocardial surface of the left ventricle (LV) for a full cardiac cycle. This reconstruction framework captures the motion of the full 3D surfaces of the complex anatomical features, such as the papillary muscles and the ventricular trabeculae, for the first time, which allows us to quantitatively investigate their possible functional significance in health and disease.