Springer Verlag, Lecture Notes in Computer Science, p. 280-291
DOI: 10.1007/978-3-642-38868-2_24
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We propose a new approach for statistical shape analysis of 3D anatomical objects based on features extracted from skeletons. Like prior work on medial representations [7,15,9], the approach involves deforming a template to target shapes in a way that preserves the branching structure of the skeleton and provides intersubject correspondence. However, unlike medial representations, which parameterize the skeleton surfaces explicitly, our representation is boundary-centric, and the skeleton is implicit. Similar to prior constrained modeling methods developed 2D objects [8] or tube-like 3D objects [13], we impose symmetry constraints on tuples of boundary points in a way that guarantees the preservation of the skeleton's topology under deformation. Once discretized, the problem of deforming a template to a target shape is formulated as a quadratically constrained quadratic programming problem. The new technique is evaluated in terms of its ability to capture the shape of the corpus callosum tract extracted from diffusion-weighted MRI. © 2013 Springer-Verlag.