Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
International Journal of Computer Vision
Comparison of Cardiac Motion Across Subjects Using Non-rigid Registration
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Inter-subject modelling of liver deformation during radiation therapy
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Conditional shape models for cardiac motion estimation
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
An Elasticity-Based Covariance Analysis of Shapes
International Journal of Computer Vision
4D shape priors for a level set segmentation of the left myocardium in SPECT sequences
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Searching for linear dependencies between heart magnetic resonance images and lipid profiles
Algorithms and Applications
Image registration and atlas-based segmentation of cardiac outflow velocity profiles
Computer Methods and Programs in Biomedicine
Large scale left ventricular shape atlas using automated model fitting to contours
FIMH'13 Proceedings of the 7th international conference on Functional Imaging and Modeling of the Heart
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In this paper we present a novel method for building a 4D statistical atlas describing the cardiac anatomy and how the cardiac anatomy changes during the cardiac cycle. The method divides the distribution space of cardiac shapes into two subspaces. One distribution subspace accounts for changes in cardiac shape caused by inter-subject variability. The second distribution subspace accounts for changes in cardiac shape caused by deformation during the cardiac cycle (i.e. intra-subject variability). Principal component analysis (PCA) have been performed in order to calculate the most significant modes of variation of each distribution subspace. During the construction of the statistical atlas we eliminate the need for manual landmarking of the cardiac images by using a nonrigid surface registration algorithm to propagate a set of pseudo-landmarks from an automatically landmarked atlas to each frame of all the image sequences. In order to build the atlas we have used 26 cardiac image sequences from healthy volunteers.We show how the resulting statistical atlas can be used to differentiate between cardiac image sequences from patients with hypertrophic cardiomyopathy and normal subjects.