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2006
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A tightly coupled region-shape framework for 3D medical image segmentation

10 years 3 months ago
A tightly coupled region-shape framework for 3D medical image segmentation
Most hybrid 3D segmentation methods either heuristically couple the respective algorithm or combine a true 3D with a 2D algorithm due to computational considerations. In this paper we propose a new probabilistic framework for 3D image segmentation that combines tightly linked region- and shape-based constraints. Regionbased label constraints are modeled by a 3D Markov random field, and are tightly coupled to shape-based constraints of a 3D Deformable Model. The full 3D nature of the combined model leads to a robust smooth surface segmentation that outperforms the single constraint, slice-based as well as the loosely coupled 3D methods.
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2006
Where ISBI
Authors Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
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