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» Level Set Methods for Watershed Image Segmentation
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SMI
2010
IEEE
167views Image Analysis» more  SMI 2010»
13 years 7 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...
DAGM
2006
Springer
14 years 15 days 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
14 years 10 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
14 years 10 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...
ECCV
2006
Springer
14 years 10 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