Average brain models: a convergence study
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Interactive Organ Segmentation Using Graph Cuts
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Variability of the human cardiac laminar structure
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Statistical atlas of human cardiac fibers: comparison with abnormal hearts
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Groupwise spectral log-demons framework for atlas construction
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Multi-resolution DT-MRI cardiac tractography
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Patient-specific models of cardiac biomechanics
Journal of Computational Physics
Moving frames for heart fiber geometry
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
Spectral Log-Demons: Diffeomorphic Image Registration with Very Large Deformations
International Journal of Computer Vision
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A statistical atlas of the cardiac fiber architecture is built for the first time with a human dataset of 10 healthy ex vivo hearts acquired using DT-MRI. The atlas is constructed using an efficient semiautomated method where limited interactions are only required to segment the myocardium. All hearts are registered automatically by an efficient and robust non linear registration method. The statistical atlas gives a better understanding of the human cardiac fiber architecture. The study on the global variability of the human cardiac fiber architecture reveals that the fiber orientation is more stable than the laminar sheet orientation. The variability is also consistent across the left ventricular AHA segments. Moreover this atlas could be used for cardiac electromechanical modeling as well as a basis for more precise extrapolation models, essential for in vivo cardiac DT-MRI acquisition.