Medical image segmentation using topologically adaptable surfaces

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Medical image segmentation using topologically adaptable surfaces
E cient and powerful topologically adaptable deformable surfaces can be created by embedding and de ning discrete deformable surface models in terms of an A ne Cell Decomposition (ACD) framework. The ACD framework, combined with a novel and original reparameterization algorithm, creates a simple but elegant mechanism for multiresolution deformable curve, surface, and solid models to \ ow" or \grow" into objects with complex geometries and topologies, and adapt their shape to recover the object boundaries. ACD-based models maintain the traditional parametric physics-based formulation of deformable models, allowing them to incorporate a priori knowledge in the form of energy and force-based constraints, and provide intuitive interactive capabilities. This paper describes ACD-based deformable surfaces and demonstrates their potential for extracting and reconstructing some of the most complex biological structures from medical image volumes.
Tim McInerney, Demetri Terzopoulos
Added 07 Aug 2010
Updated 07 Aug 2010
Type Conference
Year 1997
Authors Tim McInerney, Demetri Terzopoulos
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