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» A probabilistic framework for image segmentation
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CVPR
2009
IEEE
13 years 12 months ago
Classification of tensors and fiber tracts using Mercer-kernels encoding soft probabilistic spatial and diffusion information
In this paper, we present a kernel-based approach to the clustering of diffusion tensors and fiber tracts. We propose to use a Mercer kernel over the tensor space where both spati...
Radhouène Neji, Nikos Paragios, Gilles Fleu...
BILDMED
2008
188views Algorithms» more  BILDMED 2008»
13 years 9 months ago
4D Endocardial Segmentation Using Spatio-temporal Appearance Models and Level Sets
In this paper a framework for the segmentation of cardiac MR image sequences using spatio-temporal appearance models is presented. The method splits the 4D space into 2 separate su...
Karl D. Fritscher, Rainer Schubert
CVPR
1997
IEEE
14 years 7 days ago
Area and Length Minimizing Flows for Shape Segmentation
— A number of active contour models have been proposed that unify the curve evolution framework with classical energy minimization techniques for segmentation, such as snakes. Th...
Kaleem Siddiqi, Steven W. Zucker, Yves Béru...
MICCAI
2009
Springer
14 years 9 months ago
Setting Priors and Enforcing Constraints on Matches for Nonlinear Registration of Meshes
Abstract. We show that a simple probabilistic modelling of the registration problem for surfaces allows to solve it by using standard clustering techniques. In this framework, poin...
Benoît Combès, Sylvain Prima
NIPS
2007
13 years 9 months ago
Learning Visual Attributes
We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ...
Vittorio Ferrari, Andrew Zisserman