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» Level Set Methods for Watershed Image Segmentation
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139
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SMI
2010
IEEE
167views Image Analysis» more  SMI 2010»
15 years 1 months ago
RBF Dipole Surface Evolution
—The level set method can implement a wide variety of shape modeling operations (e.g. offsetting, skeletonization, morphing, blending, smoothing, sharpening, embossing, denoising...
Yuntao Jia, Xinlai Ni, Eric Lorimer, Michael Mulla...
135
Voted
DAGM
2006
Springer
15 years 6 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
CVPR
2008
IEEE
16 years 4 months ago
A statistical deformation prior for non-rigid image and shape registration
Non-rigid registration is central to many problems in computer vision and medical image analysis. We propose a registration algorithm which is regularized by prior knowledge in th...
Marcel Lüthi, Thomas Albrecht, Thomas Vetter
ECCV
2006
Springer
16 years 4 months ago
Segmentation of High Angular Resolution Diffusion MRI Modeled as a Field of von Mises-Fisher Mixtures
High angular resolution diffusion imaging (HARDI) permits the computation of water molecule displacement probabilities over a sphere of possible displacement directions. This proba...
Tim McGraw, Baba C. Vemuri, Robert Yezierski, Thom...
140
Voted
ECCV
2006
Springer
16 years 4 months ago
Random Walks, Constrained Multiple Hypothesis Testing and Image Enhancement
Image restoration is a keen problem of low level vision. In this paper, we propose a novel - assumption-free on the noise model - technique based on random walks for image enhancem...
Noura Azzabou, Nikos Paragios, Frederic Guichard